Healthcare

Research and innovation addressing today's greatest health challenges

Introducing IBM Research’s 2019 Fellows

Congratulations to the entire class of 2019 IBM Fellows.

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Could Mitochondria Numbers Be the Key to Solving Cancer Drug Resistance?

New research shows that the number of mitochondria in a cell is associated with drug resistance, which could have a far-reaching impact in cancer treatment.

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Using Machine Learning to Develop Blood Test For Key Alzheimer’s Biomarker

Alzheimer’s disease, a terminal neurodegenerative disease, has historically been diagnosed based on observing significant memory loss.

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The Fundamentals of Mass Transport in Biopatterning

The patterning of molecules is critical in applications including microarrays, tissue engineering, biosensors, biomaterials and fundamental cell studies.

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Biophysics-Inspired AI Uses Photons to Help Surgeons Identify Cancer

Biophysics-inspired AI tools would provide a richer amount of information to support intraoperative decisions of surgeons during removal of cancerous tissue.

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Understanding Parkinson’s Disease with Machine Learning and The Michael J. Fox Foundation

IBM’s collaboration with The Michael J. Fox Foundation aims to better understand Parkinson's disease (PD), a chronic, degenerative neurological disorder.

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Fingernail Sensors and AI Can Help Clinicians to Monitor Health and Disease Progression

Grip strength is a useful metric in a surprisingly broad set of health issues. It has been associated with the effectiveness of medication in individuals with Parkinson’s disease, the degree of cognitive function in schizophrenics, the state of an individual’s cardiovascular health, and all-cause mortality in geriatrics. At IBM Research, one of our ongoing challenges […]

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Could AI Help People Change Their Behaviour?

An open-source AI algorithm to help people change their behaviour, based on an ontology developed by behavioural scientists at University College London.

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Evolving Speech and AI as the Window into Mental Health

Mental health and neurological disorders are a growing epidemic. In the U.S., nearly one in every five people has a mental health condition (1). Yet there is a growing shortage of mental health professionals to adequately treat this need. By 2025, it’s estimated that demand for psychiatrists may outstrip supply by up to 15,600 psychiatrists […]

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AI and the Eye: Deep Learning for Glaucoma Detection

Glaucoma is the second leading cause of blindness in the world, impacting approximately 2.7 million people in the U.S alone [1]. It is a complex set of diseases and, if left untreated, can lead to blindness. It’s a particularly large issue in Australia, where only 50% of all people who have it are actually diagnosed […]

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Towards Language Inference in Medicine

Recent times have witnessed significant progress in natural language understanding by AI, such as machine translation and question answering. A vital reason behind these developments is the creation of datasets, which use machine learning models to learn and perform a specific task. Construction of such datasets in the open domain often consists of text originating […]

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Painting a Clearer Picture of the Heart with Machine Learning

Coronary Artery Disease (CAD) is a condition in which plaque forms on the walls of coronary arteries, causing them to narrow. Eventually, this could lead to a heart attack, or death. This condition is now the single largest health problem in the world, with over one million people in the US undergoing cardiac catheterization – […]

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