DTs for Autonomous Driving and Collision Avoidance

With the modernization and over population the resource utilization is enhancing frequently and soon we will see the replenishment of the utility resources. Innovations and inventions in every sector and area have led to some advantages and disadvantages. Today we will talk about the digital innovations to overcome or avoid chances of collision which might result in serious mishaps. There are various methods which verifies safety like the Hamilton-Jacobi method which is used to provide safety assurance from collision. Here we will put some light on the power of trajectory which will propose a framework for prediction based reachability by using computing safety controllers.

The use of safety controller is based on various parameters like :

  • Implementation Mode
  • Conservative Action Set
  • Trajectory Prediction
  • Proposed Mode
  • Predicting Classifier
  • Deploy Safety Controller
  • Simulations in T-intersection

Autonomous Driving and Collision Avoidance
Autonomous Driving and Collision Avoidance

Various Adaptive Automated Surrogate Modelling :

With the help of AEB and ACC the Department of Transportation Safety Pilot Model Deployment database is running effectively and helpful in demonstrating or evaluating the collision avoidance reliability by using in house built Advanced Driver Assist Systems. 

ACC is a control automatically provided to adjust the speed and distance from the vehicle going ahead. It is facilitated by cruise control advanced driver assistance systems and in 2019 was represented with 20 different names based on functionality. Control Sensor is the primary source of information regulated by radar, laser and camera to detect the car approaching another vehicle. This technology is the face of future intelligent car generation. Level 1 autonomous cars (self assist) are the best examples of autonomous cruise control vehicles in combination with another driver assist feature (Lane centering) called Level 2 autonomous car.

AEB is a system which can identify potential forward collision and by applying vehicle braking actively can de-accelerate the mitigating collision. They provide an alert or warning to the driver by detecting the impending collision through sensors and efficiently function without the presence of the driver even. At low speed collision can be avoided by applying braking, at higher speed collision can be avoided by steering (is a new concept) depending upon the clearance of the lane.

There are three main collision warning :

  • Autonomous
  • Emergency
  • Braking

In order to avoid collision reliability analysis method is equipped with autonomous emergency braking (AEB) & adaptive cruise control (ACC) and this method is consist of two elements named :

Model Based Reliability Analysis – After Uncertainty Modelling method an adaptive surrogate modelling method is opted for active learning function effectively and precisely to avoid collision avoidance reliability

Uncertainty Modelling of Traffic Conditions – In this method to capture complicated correlations we use real world data with different variables and a newly developed Gaussian mixture copula (GMC) method  is implemented to showcase uncertainty in road traffic conditions.

Road Transport Through Lane Departure :

In this mechanism, warnings are given to the drivers to move out of its lane to minimize the accidents by any means like distractions, error and drowsiness etc. Depending upon National Highway Traffic Strategy Administration there are three types of departure warning systems

  • Systems to warn the driver if leaving its lane
  • Systems to warn the driver with no response to lane
  • Systems to assist oversteering and taking take over in challenging situations

Intelligent DT & IoT-Based Service for Smart Cities

With the growing population there will be an enormous and abundant need of resources so that humans can sustain their life smoothly in upcoming years. Proper resource utilization plays an important role in structuring smart cities with all the adequate resources in hands. IoT has emerged as an ultimate resource in the smart cities revolution, without human involvement. Billion trillions devices are interconnected to collect and identify huge volumes of data and can be managed by cloud computing processing, management and storage will include security risks as well. In order to manage the sudden urge of supportive resources of a growing population, rising technology comes into picture. IoT evolution studies have presented an analytical network process which works on complexity with alternatives for smart city evaluation.

Parameters to be addressed for Smart City :

  • Wireless Connectivity
  • Security
  • Open Data
  • Monitoring Control

Service Platforms and Architecture of Smart Cities
Service Platforms and Architecture of Smart Cities

By 2050 , the population will increase by 2.5 billion and in the coming years the cities will be occupied by 68% of population, which gives a challenging issue to be resolved by implementing the modern digital transformations, innovations and inventions by opting sustainability principles and management of urban areas development. Sadhukan, Sabrina has proposed a framework based on structural relationship based access control managed by blockchain and provide smart control to the internal users of organizations. Service platforms and architecture help in analyzing applications associated with case study of smart cities in collecting generic data and roadmaps of directions to get advanced cities by mapping access control.

Disciplines where IoT can be Implemented :

Smart Cities Innovation Center is used to quantify data flow and to detect sensors through 5G networks connected through WiFi & smartphones. IoT can be implemented to multidisciplinary sectors to obtain the following Innovations :

  • Smart Healthcare Sector
  • Smart Homes
  • Smart Surveillance
  • Smart Environment
  • Smart Transportation
  • Smart Agriculture

Smart City is an infrastructure framework which provides sustainable development practices by implementing wireless cloud technologies like smartphones, connected cars, traffic lights, street lightning, and smart garbage to improve quality of life. Many countries are determined to set goals in managing sustainable development. Ecosystem can be improved by taking following into consideration :

  • Managing proper trash collection
  • Energy distribution
  • Mobility
  • Optimizing infrastructure
  • Lower the traffic congestion.

Low Power Wide Area Network (LPWAN) technologies are best suited for smart cities while others can include  LoRa, LTE Cat M, Bluetooth, NB-IoT and 5G Technology will lead this innovation of smart city to a greater height. 

Advantages of IoT :

  • IoT can be used for creative and innovative management which results in controlling and monitoring information through various applications of cloud data management and storage.
  • With IoT some activities can be monitored and managed which were not feasible previously by any means.
  • Cost effectiveness is the third advantage and can be reduced and optimized
  • It can be used for tracking large numbers of daily tasks with the help of smart devices.
  • It enhances the options for consumers to use diagnostics and smart devices efficiently

DT-Based Concepts for Smart Building and Smart Home

Everyday is full of innovation and inventions in computer sciences, biomedical field, communication field and engineering. Recent technology is to design a smart home by implementing technological innovations. A smart home can be connected with a local server with remote access interface and can take control of alarm security, inventory, facility management through internet access.  A smart home must includes the below features:

  • Multimedia
  • Networking
  • Entertainment
  • Communication
  • Healthcare
  • Security
  • Power
  • Energy

It is a system that provides tracking of the overall activity of your home along with the family members with medical and statistical analysis. It is also connected with FRID for grocery and integrated with TV, cables and wireless internet gateway by adopting UML method as modelling tool which connects with database design, UI Interface, inter-process communication. Home server must connect with a server with integrated functions.

Smart Home & Smart Building Infrastructure
Smart Home & Smart Building Infrastructure

Design and Integration :

The mechanism of peripheral integration belongs to methodologies, tools, XML, remote configuration, management, life cycle support and device testing. TR-069 a standard configuration mechanism based on which a smart home automation system is developed by implementing XML technology.  

With this method, all the electrical facilities along with automatic configuration server and residential gateways, the interface is controlled by remote controller through WAN. MySQL is opted as a database engine to provide end to end point communication gateway.  RFID technology is helpful in reading data tracking which is installed near warehouses. MCU takes data from an RFID reader and converts the data with the help of the device connected with the MySQL server.

Following main features of smart home devices are as follows :

  • Alarm Security
  • Tracking and Positioning
  • Facility Management
  • E-Health Profile
  • Daily Scheduler

Machine learning is also applied in smart building applications. In both the categories the solution is being presented, discussed and compared with respect to the common goals, perspectives and research trends. The two main approaches are as follows : Occupant-centric and Energy/Devices centric. 

In Occupant Centric following are the process involved :

  • Firstly, it can be used in estimation and identification processes. 
  • Secondly for activity recognition or suspension. 
  • Thirdly, in estimating preferences and behavior.

In Energy/Devices centric following are the process involved :

  • Energy Profiling
  • Demand Estimation
  • Appliances profiling
  • Fault Detection
  • Inference on sensors

A smart environment will occupy a variety of domains like smart infrastructure, transformation, resource management, precision agriculture, smart buildings etc. The IoT revolution led to an advanced energy management system in buildings. Various IoT based automated systems are available like Twine, Vera, Smartthings, openHAB, Ninjablocks, Microsoft lab Things etc.

HDTH-Based Intelligent Healthcare Systems

IoT is well known for its technical advancement in resolving real world problems by implementing biomedical engineering along with parallel computing domains with diversified applications. It is a dynamic collection of sensors, cloud storage and multiple embedded devices for data exchange by evolving remarkable shifts in robust intelligent systems. Just by using sophisticated sensors the life of patients will not improve so as to ensure the critical situations data will be stored on a cloud server and analyzed by healthcare professionals through online consultation.

Importance of Deep Learning and Neural Networks :

Neural computing, Deep learning are in high demand because of architecture made of multi-layer artificial neural network.It acquire qualities and knowledge just similar to the human brain in learning new things like speech recognition, language processing and data analysis in research. IoT is also used in patient monitoring and in aiding wearable medical devices. The data generated is beyond our control hence we would require a system that will manage data in a suitable manner. Technology and medical science are proving better means for the healthcare sector.

Intelligent Healthcare Systems
Intelligent Healthcare Systems

Deep learning is the first choice for data analysis and image processing through ECG, EEG MRI, CT, Angiography, X-ray images, etc. It is helpful in providing good and efficient  results with a greater speed in chronic situations. It is an evolving field for researchers to cover multidisciplinary topics of any field and areas. 

There are many inventions going nowadays on different topics related to IoT and some of them are as follows :

  • IoT sensors for smart healthcare devices
  • Telemedicines
  • Data Security in healthcare
  • ECG Classification using Deep learning
  • EEG Classification using Deep learning
  • Medical Image Classification using Deep learning
  • Medical Image Segmentation using Deep learning
  • Medical Image fusion using Deep learning

Various countries are adopting IoT worldwide for improving and managing the dynamic, heterogeneous, multi-source data with great velocity to improve the critical medical conditions. Managing the data will lead to integrating, collecting, processing, analyzing, extracting knowledge by proceeding with the challenging task in progressive manner. But healthcare sector is quite challenging for IoT to come up with a device or an application that will fulfill patient need in real time and conditions with certain parameters. In order to proceed with this challenge Hadoop based Intelligent system (HICS) came into existence that uses IoT and contextual big data in the healthcare system which is connected to an enormous network connected with millions of devices to gather data.

Procedure of Data Analysis :

The collected data then processed with sensors, wearable devices, connected with the patient body and forwarded them to Intelligent building(IB) through PMD (primary mobile device) by using the internet. After analyzing the data the parameters are set to identify the seriousness and abnormality of a patient. They use publicly available medical sensors in real time traffic by using statistical methods, thresholds and machine learning techniques. IB consists of 3 main parts :

  • Big Data Collection used for collection, filtration and load balancing
  • Hadoop processing Unit used for file distribution and MapReduce
  • Analyze the situation and perform actions
  • Decision Making are equipped with medical expert system

New Revolution – Industry 5.0 Production Model

We have already discussed robotics, machine learning and artificial intelligence in our previou blogs for your better understanding of the technological world. We are again here with the new version of automation technology IOT Industry 5.0 which focuses on machine and human interactions. Big data and IoT are the technologies helping humans in soothing their work by better and faster means. It is an advantage to Industry 4.0 automation.

Advantages of Industry 5.0

  •  Responsive Environment
  •  Increased Productivity
  •  Profitability
  •  Adaptability
  •  Readiness
  •  Agility
  •  Cost Reduction
  •  User Friendly

These innovations are very complex and tedious for the environment to accept. This is a process which automates the real time data and is able to process the same in the manufacturing field. Based on the types of manufacturing automation industries are of four types :

  • Primary
  • Secondary
  • Tertiary
  • Quaternary

New Revolution - Industry 5.0
New Revolution – Industry 5.0

Main 5th IR Revolutions are as follows :

  • Machine Learning
  • Mobile Technologies
  • Social Networking

What is Industry 4.0 ?

It is a trending automation and data exchange technology like cyber systems, IoT, cloud computing etc. It is also known as IIoT / Smart manufacturer performing smart functions of production and operations digitally by using machine learning, artificial intelligence and big data so that companies can focus on supply chain management. A project named High tech strategy of German originated “Industrie 4.0” which was later on changed to I4.0 or simply I4 in 2011.

Main Industrial Revolutions are as follows :

  • Coal
  • Gas
  • Electronics
  • Nuclear
  • Internet
  • Renewable Energy

At the moment we are in the fourth industrial revolution leading to industrialization and automation to generate smart goods with efficiency and efficacy. It connects the end-to-end process of production and execution to reach a new level of revolution by connecting and adapting changes.

4IR Technology is a combination of multiple technologies and a blend of interconnectivity between digital, physical and biological entities  :

  • AI
  • Robotics
  • IoT
  • Genetic Engineering
  • Quantum Computing

IR 4.0 has been implemented in the education sector and aimed at improving graduates driven capabilities in the digital industry. It is also helpful in making faster and smarter decisions to boost the profitability and efficiency

What is Industry 3.0 ?

In 1970, the third revolution came into existence by using electronics and IT automation protocols. Main areas of digital transformations are :

  • Participation
  • Data collection
  • Process Involved
  • Technology Used
  • Organizational procedure

Augmented Reality and Virtual Reality

AR is a science to demonstrate digital elements to live by using real world settings such as smartphone cameras while VR is a complete virtual demonstration of the immersion experience without the involvement of the physical world. AR enhances the virtual and real world whereas VR enhances fictional reality. VR is immersive in nature and is restricted to the specific user while AR offers more freedom to the user and will create an engaging market.

Mechanism of AR & VR :

VR immerse in fully computer simulated reality with a headphone or headset cutting down the real world. VR is not good for eyes as it is related to simulations of an imaginary world and can cause eye strain. VR is of three types based on simulations :

  • Non-Immersive
  • Semi-Immersive
  • Fully Immersive

Augmented Reality and Virtual Reality
Augmented Reality and Virtual Reality

Some Examples of VR Simulations : This concept is not only limited to the below examples as other leading big benches are also the leading players who can surprise anytime with the new invention in the field of immersion and usability like Apple, Google,  Lenovo, Samsung.

  • HTC Vive Pro Eye
  • Oculus Quest and Playstation

The final goal of VR is to build a human with spoken language, drawing pictures and writing letters etc. In the current scenario VR is on demand due to generations habitual of games with best innovative controls, well supported ecosystem. 

Elements of VR :

  • Comfort
  • Video Games
  • Education
  • Sensors
  • Interaction
  • Immersion

VR can lead to brain damage and can develop symptoms like depression, dizziness and collapse of vision, disorientation that occur due to VR experience. It also affects the pattern and quality of sleep.

Disadvantages of VR :

  • Lack of Flexibility
  • Quite Expensive
  • Functionality Issue
  • Addiction to Virtual World

Advantages of VR :

  • No risk
  • Realistic Scenarios
  • Simplifies Complex Problems
  • Innovative
  • Managed Remotely

AR provides a virtual experience of the real world. It revolves around images, text and sounds and got attention in 2016 with the game Pokemon Go. AR can be explored on android devices and through Google Play Store. Nearly 589 million devices are launched through AR technology in 2020. AR is tremendously used in medical training,  in MRI applications, in surgeries etc.

Some Examples of AR Simulations :

  • U.S. Army
  • Google Pixel’s Star Wars Stickers
  • Disney Coloring Book
  • L’Oréal Makeup App
  • Nintendo’s Pokémon Go App
  • Weather Channel Studio Effects
  • IKEA Mobile App

It has a growing market among mobile computing and business applications.  Similarly AR Zone app facilitates AR features like AR Emoji by creating animated versions and AR Doodle on android mobile. ARCore is a platform for AR experiences by using APIs. AR software is already installed in the smartphones with different versions.  

Some Smartphones that enabled ARCore :

  • moto g⁹ Play
  • Asus ROG Phone III
  • Nokia8.3 5G
  • LG K71
  • Infinix Mobile Zero 8
  • motorola one 5G
  • OnePlus Nord

Latest Artificial Intelligence Apps for iOS and Android.

We are progressing gradually in the field of innovation and are creating valuable insights with each passing day. Technology is imparting a fruitful combination to humans all together in terms of information exchange, solving mankind problems, making tasks easier and promoting development. The modern innovation blend of the technology era is to make our lives beneficial and convenient. To feel secure in every phase of your life you need technology for both personal and business point of view.

Impact of Technology in Human Life :

Due to technology the pace of life is increasing with increased communication, travelling, action and interactions to speed up life. Benefits of technology can be improved by test grades, scores, creativity, problem solving skills, special needs, acquiring knowledge. Technology is expanding its arms in vivid areas with proven advantages and inventions. With advantages there lies disadvantages as well like crime and terrorism, social disconnect, privacy concerns. work overload, job insecurity and complexity.

Techniques implemented in AI :

  • Machine Learning
  • Automation and Robotics
  • NLP -(Natural Language Processing)
  • Machine Vision

Latest AI Applications
Latest AI Applications

Artificial intelligence is the process of simulation of human intelligence through machines. Machine vision, language processing, speech recognition and expert systems are few applications of AI. If we consider examples then social media is the biggest one as it provides the content to suggestions. The purpose of AI is to perform complex tasks like problem solving, decision making, understanding human communication and perception into the simpler one. There are four types of AI and it can be weak AI(facebook newsfeed), strong AI and artificial AI

  • Relative Machines
  • Limited Memory
  • Theory of MInd
  • Self Awareness

Scope of AI in future :

It has a tremendous impact on human life by exploring new technological innovations like big data, robotics and IoT. A supercomputer named Perlmutter for NERSC is the most powerful and giant AI machine in the world. Siri is the form of AI System that uses artificial intelligence. It also has a negative impact and can be used as a devastating system as well. It is nowadays be implemented in every sector like :

  • Retail
  • Security
  • Fashion
  • Shopping
  • Production
  • Sports Analytics
  • Manufacturing

In terms of the future it will help to analyse the patient data in the healthcare sector, in diagnosing brain tumors and finding the best possible solution to it. It will lead to revolution in the pharmaceutical area. It is a promising career with lots of opportunities in hand with justifiable salary and growth in future. Hanson Robotics is the most advanced robot till date. Ohn McCarthy is the father of Artificial Intelligence who devised a hydraulic orange squeezer. China is the only country across the globe that uses AI at a greater pace and is a leader by raising it from 4.26% to 27.68% in 2017.

Few top notch AI Softwares are :

  • Google Cloud Machine Learning
  • Content DNA Platform
  • H2O.AI.
  • IBM Watson
  • TensorFlow
  • Azure Machine Learning Studio
  • Cortana

The main algorithm applied in AI power systems are :

  • Fuzzy logic system
  • Simulated Optimization
  • Genetic Algorithm
  • Colony Optimization
  • Artificial Neural Network
  • Evolutionary Computing
  • Simulated Annealing
  • Particle Swarm Optimization

Facial Recognition by Implementing Artificial Neural Network Algorithm

It is a technology capable of comparing  a human face from a digital image and video frame against the collected database of different faces. It helps in authenticating personnel identification through ID verification services by measuring facial features with the provided image. A computer application is widely used in smartphones and robotics  nowadays. Biometrics is the best example of this type of facial recognition system but is not so accurate as compared to iris recognition and fingerprint recognition, Voice recognition, digitization of veins in the palm and behavioural measurements but is widely accepted because of the contactless process. This system is used in human computer interaction, law enforcement agencies, indexing of images, and video surveillance  

Background of the Technology :

If we dig deep down in history the discovery was started in the 1960s by Charles Bisson and he named his project “man-machine”. Later in 1970, Takeo Kanade invented a face matching system that locates anatomical features like chin and calculates the distance ratio. In 1993, Defense Advanced Research Project Agency (DARPA) and Army Research Laboratory (ARL) invented a program FERET to assist with intelligence security. The Department of Motor Vehicles (DMV) used the first automated facial recognition system for photo identification in driving licence.

Facial Recognition By AI
Facial Recognition By AI

Methods used for face recognitions :

It is such a challenging task to identify a human face with the help of 3D and 2D images. Some algorithms are used to detect facial marks or features like relative position, shape, size of nose, eyes, cheeks and jaws.

  • Traditional Algorithm approach
  • Human Identification at a distance
  • 3D Recognition
  • Thermal Cameras

Facial marks are used for facial recognition systems with some implementations in convolutional neural network architecture (CNN) systems with more accuracy.  They are combined with FaceNet facial recognition system in order to seek better performance. There are few common approaches to capture, analyse and compare patterns based on a person’s facial details. Identification and authentication are the two common keywords for facial recognition.

Facial Emotion Recognition (FER)

It is used for mapping expressions to detect emotions such as joy, surprise, fear, anger, sadness with the help of image processing software.

  • Face Detection
  • Face Capture
  • Face Match

Facial Biometrics, 2D, 3D sensor captures the face and transforms into digital data by using an algorithm for comparing images with database images. These automated systems can be used to identify a person quickly even in a crowd within a dynamic environment. All the top notch software companies are regularly working on AI, image recognition and face recognition. Some of the big faces are :

  • Academia
  • Facebook
  • Google
  • Amazon
  • Microsoft
  • IBM
  • Megvii

Facial expression can be detected by artificial neural network algorithms. It generates a great revenue globally with an estimation of $3.2 billion. The most significant vendor for facial recognition include :

  • Aware
  • BioID
  • Certibio
  • Nuance
  • Idemia
  • Leidos
  • M2SYS
  • NEC
  • Fulcrum Biometrics
  • Thales
  • Phonexia
  • Smilepass
  • HYPR
  • Fujitsu

Telemedicine in Healthcare Sector

It is a medicine practice by implementing technology also known as telehealth or e-medicine which provide healthcare services, care, advice, exams, reminders, interventions, monitoring, remote admissions and consultations. It results in evaluating, treating and diagnosing a patient at a distant place. It offers an opportunity to the doctors or physicians to treat them anywhere by using computers and software. It is very useful in benefiting both healthcare personnel and patients.

Telemedicines are of three types :

  • Remote Monitoring
  • Store and Forward
  • Real Time Interactive Services

How does it Work :

To gain a better long term patient satisfaction and care management system we need telemedicine healthcare services to locate health information and communicate with healthcare professionals. If anyone needs health assistance through telemedicine they need to fix an appointment at the same cost as an in person visit. It is costlier to maintain and set up the service for smaller healthcare providers. By entering a few basic background details online with contact details you can get yourself registered for a session with a doctor.

Telemedicine in Healthcare
Telemedicine in Healthcare

Procedure to get yourself register :

  • Choose Your Plan
  • Fill the form
  • Questions for Patient
  • Involvement of staff
  • Need to know about coverage
  • Use of telemedicine
  • Should Know the regulations

To prevent Covid 19 spread, flu and other infectious diseases, telemedicine is the best way to keep the people safe. It can be applied to psychotherapy and teledermatology. It is a two way process of communication and can be done through video conferencing and phone consultations in real time from anywhere and anytime.

Services offered by Telemedicine :

  • Transmission of Image
  • Medical Report
  • Patient Consultation
  • Medical Education
  • e-Health Patient Monitoring
  • Health Wireless Applications
  • Video Conferencing

In order to get this service you need to be technically skilled with an insurance facility so that you can make an appointment and describe your symptoms to the doctor. In a recent survey, it is revealed that telemedicine is a good aspect in keeping the care. It is although not very impactful in physical examinations in crucial cases. 

Categories of Telemedicines :

  • Telementoring
  • Teleconsultation
  • Telemonitoring

Steps involved in Virtual Visit :

  • Click on the link in an email provided by the hospital patient portal
  • Install the video software that your doctor uses
  • Allow access for audio and video

CPT and HCPCS codes are applicable to billed this service for patient virtual consent check in. 95 modifier is a synchronous telemedicine service that works on real time interactive audio and video telecommunication systems.

ML Prediction of Breast Cancer Survival

Cancer is a process of abnormal cell growth which loses contact inhibition and cease proliferation and growth of normal cells when contacting each other. The old cells of the body grow out of control and do not die resulting in abnormal growth of cells forming a mass of tissue called Tumor while leukemia do not form tumors. Lung and prostate cancer is the deadliest cancer with the highest death rates. Pancreatic cancer is a silent killer.

Major Types of Cancer :

  • Leukemia
  • Sarcoma
  • Carcinoma
  • Melanoma
  • Lymphoma

Cancer are of various types depending upon the tissues and the organs they are infecting. Breast cancer is commonly seen in women and the symptoms are lumps, thickening and swelling of part of breast, redness or flaky skin, bloody discharge from nipple and irregular shape of breast. It can be treated by radiation, chemotherapy, hormone therapy and surgery based on the stage of cancer. 

Machine Learning Algorithm in Cancer Prediction
Machine Learning Algorithm in Cancer Prediction

Symptoms of cancer :

  • Hoarseness or Nagging cough
  • Change in Bowel 
  • Persistent lumps or swollen glands
  • Blood in Urine
  • Indigestion or difficulty in swallowing
  • Unexpected vaginal bleeding or discharge
  • Blood in stool 
  • Underweight loss, fever, night sweats
  • Continued itching in genital area

How does it occurs :

When normal breast cells begin to grow abnormally than healthy cells do, forming a lump or mass can easily spread to other parts of the body through lymph nodes. Through the ACS report the lumps can be easily seen. The division process may involve 28th to 30th cell division cycles to get detected. In malignant cancer the use of logistic regression machine learning technique has been implemented to detect the tumorous cells.

ML can be used to predict breast cancer in clinical practices with low to high accuracy. ML suggests an alternative prediction modelling approach to address the current situations and to improve the limitations. In order to predict the tumor cells deep learning techniques have been used with various activation functions like :

  • Tanh
  • Maxout
  • Exprectifier
  • Rectifier

SVM technique is suitable to identify the type of cancer if it is malignant or beginning based on tumor cell size. It is a branch of data science that uses an algorithm to sequence statistical data in a programmed manner.

ML Methods for automatic diagnosis of cancer

  • Novel Methods for image classification / segmentation
  • ML based Models for detection / prediction
  • Cancer image analysis
  • Data generation for cancer diagnosis
  • Mobile applications for detection / prediction

AI can be used in cancer predicting processes by applying various fields like ML, Neural networks, Evolutionary Computation, Vision, Speech Processing, Expert Systems, Natural Language Processing, Robotics and Planning. We can detect breast cancer through screening tests like mammograms, like an X-ray to detect cancer up to two years.

Cancer Survival Rate in Breast Cancer :

The average survival rate with non metastatic Invasive breast cancer is 90% (5-year Survival rate)
The average survival rate with non metastatic Invasive breast cancer is 84% (10-year Survival rate)
The average survival rate with non metastatic breast cancer is 99% (5-year Survival rate)