Machine Learning to Fight Antimicrobial Resistance

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.

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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

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7 Limitations of Molecular Docking & Computer Aided Drug Design and Discovery

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

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Artificial Intelligence for Balance Control and Fall Detection of Elderly People

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

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Artificial Intelligence to Combat Antibiotic Resistant Bacteria

Antibiotic resistance bacteria is becoming world’s biggest health crisis. Dr. Amit Ray explains how artificial intelligence can be used in combating antibiotic resistant bacteria. A multi-agent deep reinforcement learning models for predicting behavior of bacteria and phages in multi-drug environments are discussed.

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Artificial Intelligence and Blockchain for Precision Medicine

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.

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Artificial Intelligence in Precision Medicine

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

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Artificial Intelligence in Radiology

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

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