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Integration of ML in the diagnosis and treatment of neurodegenerative diseases

A recent Nature review, describes the latest developments in the use of machine learning approaches to interrogate datasets in neurodegenerative […]

ML-based approach for drug synergy predictions and stratification

Particularly in oncology, combination drug treatments can offer higher patient survival rates and a lower risk of drug resistance than […]

First end-to-end autoML pipeline for time-series data

The van der Schaar lab has announced the release of their alpha version of clairvoyance, an autoML complete package for […]

Immunai secures $20M in seed funding to map immune system using ML

Immunai, a biotech start-up founded by MIT, Harvard and Stanford researchers, has emerged from stealth mode with $20 million in […]

Lessons from building an end-to-end ML platform

Caleb Kaiser, writing for Towards Data Science, shares his experience of trying – and failing – to build an end-to-end […]

Challenges for ML algorithms in COVID-19 drug screening

AI Cures, the newly-conceived contribution of MIT J-Clinic to COVID-19 research, aims to develop machine learning methods to discover antiviral […]

AstraZeneca: Formulating your problem to best leverage ML

Last October, at D4 USA, Gerald Sun, Senior Data Scientist, AstraZeneca, demonstrated how to get more out of convolutional neural […]

ML identifies epigenetic markers of Schizophrenia

We know from twin studies that Schizophrenia carries a 80% heritability risk, but haven’t yet managed to deduce exact genetic […]

How is AI accelerating drug development?

The first entirely AI-developed drug candidate, DSP-1181, entered Phase I clinical trials in Japan earlier this year, having been discovered […]

Moving towards machine learning engineering

Over the last few decades, we have made giant leaps forward with machine learning technologies. We can now train machines […]