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What’s Holding Back Machine Learning in Healthcare

What is holding back the large scale implementation of machine learning systems in healthcare and precision medicine? In this article Dr. Amit Ray, explains the key obstacles and challenges of  implementing large-scale machine learning systems in healthcare.   Dr. Ray argued that lack of deeper integration, incomplete understanding of the underlying molecular processes of disease it is intended to treat, may limit the progress of implementing large-scale machine learning based reliable systems in healthcare. Here, nine obstacles of present day machine learning systems in healthcare are discussed. 

What Holding Back Machine Learning in Healthcare

Machine Learning in Healthcare

Recently, machine learning algorithms, especially deep learning has shown impressive performance in many areas of medical science, especially in classifying imaging data in different clinical domains. In academic environment, Deep learning and Reinforcement learning methods of Artificial Intelligence (AI) has shown tremendous success in numerous clinical areas such as: Omics data integration (such as genomics, proteomics or metabolomics), prediction of drug-disease correlation based on gene expression, and finding combinations of drugs that should not be taken together. Deep learning is very successful in predicting cancer outcome based on tumour tissue images. Machine learning are used for medical decision support systems for ICU and critical care. Artificial Intelligence in Healthcare Current Trends discusses the current status of AI in healthcare. Read More »What’s Holding Back Machine Learning in Healthcare

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. 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..