Key Artificial Intelligence Projects to Fight Against COVID-19 Dr. Amit Ray Compassionate AI Lab In our Compassionate AI Lab, we broadly classified our fight against COVID 19 Artificial intelligence (AI) based research projects into six groups. They are AI for COVID vaccine development, AI for COVID drug discovery, AI for COVID diagnosis, AI for COVID testing, AI for COVID growth rate forecasting, and AI for social robots. Researchers across the… Read More »Artificial Intelligence to Fight Against COVID-19
AI for Healthcare
The seven top machine learning projects to fight against antimicrobial resistance are explained. Antimicrobial resistance is one of the key reasons of human sufferings in modern hospitals. Preventing microbes from developing resistance to drugs has become as important issue for treating illnesses across the world. Artificial Intelligence, machine learning, genomics and multi-omics data integration are the fast-growing emerging technologies to counter antimicrobial resistance problems. Here, Dr. Amit Ray explains how these technologies can be used in seven key areas to counter antimicrobial resistance issues.
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.
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
7 Limitations of Molecular Docking & Computer Aided Drug Design and Discovery Over the past decades, molecular docking has become an important element for drug design and discovery. Many novel computational drug design methods were developed to aid researchers in discovering promising drug candidates. In the recent years, with the rapid development of faster architectures of Graphics Processing Unit (GPU)-based clusters and better machine algorithms for high-level computations, much progress has been… Read More »7 Limitations of Molecular Docking & Computer Aided Drug Design and Discovery
Artificial Intelligence for Balance Control of Elderly People Designing automated balance control system for elderly people is one of the key project of our Compassionate AI Lab. Here, Dr. Amit Ray discuses about one of the recent project of AI using deep learning algorithms for automatic balance control of elderly people. He explains how machine learning algorithms can be used to study and improve the dynamical properties of postural stability of… Read More »Artificial Intelligence for Balance Control and Fall Detection of Elderly People
Artificial Intelligence to Combat Antibiotic Resistant Bacteria
Antibiotic resistance bacteria is one of the key research area of our Compassionate AI Lab. Dr. Amit Ray explains how artificial intelligence can be used in combating these superbugs. Antibiotic resistance bacteria is becoming world’s biggest health crisis. We discussed here multi-agent deep reinforcement learning models for predicting behavior of bacteria and phages in multi-drug environments. We call this model as DeepCombat.
Antibiotic resistant bacteria are bacteria that are not controlled or killed by antibiotics. They are able to survive and even multiply in the presence of an antibiotic. These bacteria currently kill an estimated 700,000 people globally each year – a death toll which could rise to 10 million a year by 2050 if we don’t act . The main difficulty is that the bacteria are changing fast. They changing faster than we can change the drugs in response.
Artificial intelligence is showing alternative means of fighting these deadly infections and killer bacteria. Multi-drug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, thousands of lives lost. Artificial Intelligence for healthcare is progressing at an exponential rate. We are evaluating here, the role of artificial intelligence in fighting these superbugs. Especially, the use of AI for intelligent Phage therapy.Read More »Artificial Intelligence to Combat Antibiotic Resistant Bacteria
Here, we discussed the scopes and implementation issues of artificial intelligence and blockchain for precision medicine. Evidence-based medicine is gradually shifting from therapy to prevention and towards individually tailored precision medicine systems. Where, artificial intelligence can be used to automatically detect problems and threats to patient safety, such as patterns of sub-optimal care or outbreaks of hospital-acquired illness. Artificial intelligence can be used to prevent the issues like drug-interaction, over-diagnosis, over-treatment and under-treatment. It can be used more effectively to solve the problems of antibiotic resistant bacteria.
Artificial Intelligence in Precision Medicine Artificial intelligence in precision medicine is a revolutionary new approach advancing health and wellness, knowledge, and health care delivery to maximize the quality of life for all over a lifetime. The main concept of precision medicine is providing health care which is individually tailored on the basis of a person’s genes, lifestyle and environment. With the advances in genetics, artificial intelligence and the growing availability of health… Read More »Artificial Intelligence in Precision Medicine
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… Read More »Artificial Intelligence in Radiology