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AI in Life Sciences Group.

Artificial Intelligence in Healthcare and Medicine

A new wave of neural artificial intelligence is rapidly changing medicine and healthcare. The changes affect everyone from clinicians, predominantly via rapid, accurate image interpretation, over health systems, by improving workflow and the potential for reducing medical errors, and also patients, by enabling them to get individualized therapies to promote health. Theresa Roland, opens an external URL in a new window leads the healthcare and medicine group, which optimizes the intensive care supply with AIs, opens an external URL in a new window and further raises the quality of patient care. Together with a prostheses manufacturer the research team has improved the robustness of active hand prostheses, opens an external URL in a new window. The team of scientists has developed AIs for medical images, opens an external URL in a new window that outperform human experts and make them understandable for practitioners, opens an external URL in a new window. Currently we are investigating the potential of machine learning for predicting Covid-19 from blood laboratories.

See also: Medical cognitive computing center, opens an external URL in a new window, AI for histopathology slides, opens an external URL in a new window, GapNet, opens an external URL in a new window, AI for microscopy,, opens an external URL in a new window AI-RI, opens an external URL in a new window

 

Artificial Intelligence in Drug Design

AIs have been shown to be able to design new molecules and to accurately foresee their role in the human body. New drugs will be safer and more effective than they have ever been. Researchers of JKU have won the Tox21 Data Challenge demonstrating that neural AIs can find toxic effects. Günter Klambauer, opens an external URL in a new window leads an award-winning team, opens an external URL in a new window of scientists developing AIs that design, improve and assess new drugs. Several AI-generated drugs are currently tested for their ability to inhibit Sars-Cov-2.

See also: Tox21 Data Challenge, opens an external URL in a new window winning AI “DeepTox”, Toxicogenetics methods, opens an external URL in a new window, DeepSynergy, opens an external URL in a new window, D3Net, opens an external URL in a new window, MadeSMART, opens an external URL in a new window, Deep Learning in Drug Discovery, opens an external URL in a new window, AIDD, opens an external URL in a new window, Cheminformatics, opens an external URL in a new window, explainable AI, opens an external URL in a new window, AI-designed library of potential Sars-Cov-2 inhibitors, opens an external URL in a new window, ChemAI, opens an external URL in a new window

 

Artificial Intelligence in Molecular Biology and Genetics

Molecular biology and genetics produce an extraordinary amount of knowledge about genes, proteins and their interactions. A single run of genome sequencing produces billions of DNA snippets, for which AI methods are perfectly suited. In fact, the vast amount of information in these areas can only be handled with powerful computational methods based on artificial intelligence. The AILS research group, led by Günter Klambauer, opens an external URL in a new window, has developed cutting-edge bioinformatics methods, such as the award-winning cn.MOPS algorithm that detects variations in genomes.

See also:  Austrian Life Science Award, opens an external URL in a new window, Bioinformatics, opens an external URL in a new window, biclustering of gene expression data, opens an external URL in a new window, detection of haplotype and IBD segmen, opens an external URL in a new windowts, opens an external URL in a new window, copy number variation, opens an external URL in a new window, targeted panel sequencing, opens an external URL in a new window, computational immunology, opens an external URL in a new window