Artificial Intelligence in Healthcare Current Trends

Artificial Intelligence in Healthcare

Dr. Amit Ray, explains how artificial intelligence is changing the landscape of healthcare and modern personalized precision medicine. He also explains the current trends, scopes and concerns of AI in healthcare. Artificial intelligence (AI) quickly became an exponential technology and revolutionizing every aspect of life. The core of artificial intelligence is the ability to learn from data and the ability to adapt in changing situation and environment with high precision, accuracy and speed.  

Artificial Intelligence in Healthcare

With the increasing availability of healthcare data and rapid progress of machine learning algorithms and analysis techniques AI is gradually enabling doctors for better diagnosis, disease surveillance, facilitating early detection,  uncovering novel treatments, and creating an era of truly personalized medicine. Artificial intelligence in healthcare is going play a significant role in solving the issues like drug-interaction, false alarms, over-diagnosis, over-treatment.

There is also growing concern about how tech giants are making profit by selling personal data, including medical information. However, AI with new technologies of IoT and Blockchain has tremendous scope for better medical treatment with data security. Earlier I discussed nine key challenges of Artificial Intelligence in healthcare.  

What is Artificial Intelligence?

Artificial intelligence is defined as the branch of science and technology that concerned with the study of software and hardware to provide machines the ability to learn insights from data and environment, and the ability to adapt in changing situation with high precision, accuracy and speed.… Read more..

Artificial Intelligence in Radiology for X-Ray and CT-Scan

Artificial Intelligence in Radiology for X-Ray and CT-Scan Image Analysis 

Dr. Amit Ray
Compassionate AI Lab, Radiology Division

With artificial intelligence it is possible to analyze and interpret large amounts of radiological images efficiently. Late detection of disease significantly increases treatment costs and reduces survival rates. Often visual human interpretation of an isolated image are time-consuming, difficult and expensive. Artificial intelligence in healthcare especially in radiology has tremendous scope. Recently, AI for radiology uses deep learning, reinforcement learning, and other machine learning algorithms to systematically assess x-ray, CT Scan and MRI images of and instantly provide detailed reports on their findings.

Artificial Intelligence in Radiology

AI algorithms read medical images like a radiologist, they identify the hidden patterns in the image and relate them with medical data. The AI systems are trained using vast numbers of images like CT scans, magnetic resonance imaging (MRI), ultrasound or nuclear imaging. New AI tools that excel at medical image analysis can automatically detect complex anomalous patterns in radiological images and provide quantitative information on disease [4].

Studies have shown that computer aided screening can decrease false negatives by ~45% [1]. The AI machines reading radiology studies correctly, reaching around 95 percent accuracy [2]. The AI tools can rapidly review a number of images, prior images, patient history and other medical data, and then extract the most meaningful insights, which can then be verified by the radiologist.… Read more..

Navigation System for Blind People Using Artificial Intelligence

Do you know according to WHO, there are about 39 million people in the world who are blind? Artificial Intelligence is one of our key research area to overcome that challenge. Here, we explain the use of AI based grid cell, place cell and path integration strategies to solve the problems.

Dr. Amit Ray explains how grid cell, place cell and path integration strategies with artificial intelligence can be used  for designing the navigation system for blind people. Here, we discuss the use of AI techniques for automatic navigation. Read More »Navigation System for Blind People Using Artificial Intelligence

Brain-Computer Interface and Compassionate Artificial Intelligence to Serve Humanity

Brain-Computer Interface and Compassionate Artificial Intelligence

Dr. Amit Ray

The purpose of Compassionate AI is to remove the pain from the society and help humanity. We focused on developing AI based low cost BCI based interfaces for helping disable people.

Artificial Intelligence with Brain-Computer Interface (BCI) or Brain Machine Interface (BMI) is a fast-growing emerging technology for removing pains from the society. Here,  Dr. Amit Ray explains how with the advancement of artificial intelligence and exploration of new mobile bio-monitoring  devices, earphones, neuroprosthetic, wireless  wearable sensors, it is possible to monitor  thoughts and activities of brain neurons  and serve humanity.

This research is going to be immensely  beneficial for the physically and mentally challenged people as well as for the people who are suffering from post-traumatic stress disorder (PTSD), and other mental disorders or brain problems. Over the last 5 years, technologies for non-invasive transmission of information from brains to computers have developed considerably.

Brain-Computer Interface and Compassionate AI

Here, researchers focus to build a direct communication link between the human brain and the smartphones, earphone, computers or other devices. With BCI mind can speak silently with a smartphone or other devices.  Recent advancement of neuroprosthetic, linking the human nervous system to computers and providing unprecedented control of artificial limbs and restoring lost sensory function.

 BCI establishes two way communications between the brain and the machine.  One is  brain-computer interface and another is called computer-brain interfaces (CBI). BCI hopes to create new communication channels for disabled or elderly persons using their brain signals. Read More »Brain-Computer Interface and Compassionate Artificial Intelligence to Serve Humanity

GPUs and Deep Learning for Compassionate Artificial Intelligence

GPUs and Deep Learning for Compassionate Artificial Intelligence

Dr. Amit Ray discusses how GPUs and deep learning can be used for developing complex modules of the compassionate artificial intelligence. GPUs and cloud TPUs made complex deep learning of artificial intelligence possible in laptop, PC and smartphone. They made complex deep learning possible for research labs and smaller companies across the world. They provided a lot more computing power and efficiency for complex matrix operations and parallel processing. 

GPUs and TPUs for Deep Learning 

One of AI’s biggest potential benefits is to keep humanity healthy, happy and free from inequalities and slavery. The role of AI is gradually changing. It is shifting from typical object recognition or diagnosis tool, to complex human like powerful integrated compassionate care giving systems. Compassionate AI is one area where AI is beginning to take strong hold. Here, Dr. Ray explains the implementation of deep learning modules of integrated compassionate care giving systems with GPUs and TPUs . 

Compassionate AI GPUs and Deep LearningTraining of complex compassionate artificial intelligence modules requires deep learning neural networks. Training of compassionate modules are more time‐consuming compared to shallow learning models of AI. They may take months, weeks, days or hours depending on the size of training set and model architecture. This is because the number of computational steps increases rapidly with the number of elements in the matrix.… Read more..

Compassionate Artificial Intelligence Scopes and Challenges

Compassionate Artificial Intelligence Scopes and Challenges

With the advancement of AI and nuclear war technology, gradually mankind is moving towards a great threat. Compassionate artificial intelligence is the way to come out of that threat.  Here, Sri Amit Ray talks about how artificial intelligence, neural networks, deep learning, reinforcement learning and other machine learning technologies can be used for designing advance compassionate artificial intelligence systems. Dr. Ray discusses the scopes, issues and frameworks to include compassion, kindness and empathy in future AI systems.

Need for Compassionate Artificial Intelligence Systems

One may question why it is useful to study compassion in machines at all. Compassion is an important part of human intelligence. The main objective of AI is to serve humanity in an intelligent manner. As AI technology is improving, serving humanity on the surface level is not sufficient. AI can serve humanity in much better way in a much deeper sense.  Compassion, kindness and empathy are the components of higher human intelligence and to be true intelligent, artificial intelligence must incorporate them in the system. The scope and benefits of compassionate AI are many. Some of the requirements for compassionate AI are as follows:

Robots are leaving the realm of the industry and entering into our homes and workplaces. … Read more..

Quantum Computing and Artificial Intelligence

Quantum Computing and Artificial Intelligence

Here, Sri Amit Ray discusses the power, scope, and challenges of Quantum Computing and Artificial Intelligence in details.

In recent years there has been an explosion of interest in quantum computing and artificial intelligence. Quantum computers with artificial intelligence could revolutionize our society and bring many benefits. Big companies like IBM, Google, Microsoft and Intel are all currently racing to build useful quantum computer systems. They have also made tremendous progress in deep learning and machine intelligence.  

Quantum Computing and Artificial Intelligence

Artificial intelligence (AI) is an area of science that emphasizes the development of intelligent systems that can work and behave like humans. Quantum computing is essentially using the amazing laws of quantum mechanics to enhance computing power. These two emergent technologies will likely have huge transforming impact on our society in the future. Quantum computing is finding a vital platform in providing speed-ups for machine learning problems, critical to big data analysis, blockchain and IoT. 

The main purpose of this article is to explain some of the basic ideas how quantum computing in the context of the advancements of artificial intelligence; especially quantum deep machine learning algorithms, which can be used for designing compassionate artificial superintelligence.Read More »Quantum Computing and Artificial Intelligence

7 Limitations of Deep Learning Algorithms of AI

7 Limitations of Deep Learning Algorithms of AI

Sri Amit Ray tells us about the power and limitations of Deep Learning Architectures of Artificial Intelligence (AI).

Deep learning architectures of Artificial Intelligence has provided remarkable capabilities and advances in voice recognition, face recognition, pattern recognition, image understanding, natural language processing, game planning language translation, and search engine optimization. Deep learning is the key technology behind self-driving car. However, deep learning algorithms of AI have several inbuilt limitations. This article is focused to explain the power and limitations of current deep learning algorithms. It also provides the directions and lights to overcome the limits of deep learning algorithms to achieve higher levels learning capabilities.

Deep Learning Algorithms in AI Power and Limitations

Types of Machine Learning:

There are three core types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, the algorithm uses the training data to learn a link between the input and the outputs. It predicts the output from the trained network.  

Unsupervised learning does not use output data. It uses dimensionality reduction algorithms, Clustering algorithm, such as K-means etc. The most common unsupervised learning method is cluster analysis. Unsupervised learning algorithms can perform more complex processing tasks than supervised learning systems.


Reinforcement learning algorithms attempt to find the best ways to earn the greatest reward.… Read more..

Compassionate Artificial Superintelligence AI 5.0

Compassionate Artificial Superintelligence AI 5.0 By Dr. Amit Ray

Compassionate Artificial Superintelligence AI 5.0 by Dr. Amit RayThe book defines the concept of Compassionate Artificial Superintelligence AI 5.0.  The book explains how the emerging technologies like Internet of things (IoT), Drone, Brain-Computer-Interface, Blockchain, Big data can be used with deep learning and other modern artificial intelligence (AI) architectures for the ultimate level of joint evolution of human and machine superintelligence.  

Humans and AI systems are co-evolving. Gradually they are becoming co-dependent.  The gaps between human and AI systems are reducing. Establishing heart to heart communication is a must. Tomorrow’s AI based systems must be able to understand humans from its depth and not just fulfill the surface level requirements. Sensitivity towards human pain, mistakes, and sufferings must be the part of the evolving new AI systems.

Serving humanity intelligently is held up as the “gold standard” of AI based systems. But, with the emergence of new technologies and AI systems with bio-metric data storage, surveillance,  tracking and big data analysis, humanity and the society is facing a threat today from evilly designed AI systems in the hands of monster governments and irresponsible people.  Humanity is on the verge of digital slavery.

The aim of AI 5.0 is to build super-smart-compassionate and intelligent  society, where human and machine will co-evolve.… Read more..

Artificial Intelligence with Emotional Intelligence Issues and Challenges

Currently, deep learning modules of AI based systems lacks the emotional aspects of human intelligence. However, to fix the subjective issues like relationship, depression, anxiety and emotional issues future artificial intelligence based  systems like cyborgs require deep emotional intelligence modules.   AI is expanding and evolving itself in many technological fronts. It is not only limited by Deep learning algorithms, but expanding its horizons in deeper levels of human consciousness. Modern AI is tremendously successful for pattern recognition, voice recognition, face identification and machine learning. Self-driven cars are already on road in testing phase.  But, in today’s world AI is more needed in dealing with emotions like anger, impatience, disappointment, frustration, surprise, happiness, and gratitude. This article covers the scope, issues and challenges of AI for building emotional intelligence.

Need for Combining Artificial Intelligence with Emotional Intelligence

Human emotion is deeply associated with motivation, decision, evaluation, learning, character, intelligence, desires, and awareness. Thus, nearly all human psychological activities are subject to emotional influences and excitation. Self-awareness is the significance of the mental activities of a human being. Therefore, it should be one of the core ideas of AI with emotional intelligence.

Some researchers claims that emotional intelligence accounts for 75 percent of a person’s success and perhaps that will be more true for the success of future artificial intelligence based cyborgs and other systems. 
Read more..