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The computer model enables a better understanding of how drugs affect fibroblasts and finds a promising candidate to prevent heart scarring.
A deep learning model developed using circulating cell-free DNA outperformed traditional screening methods for gestational diabetes mellitus.
A new learning-based framework enables patients and caregivers to predict the timing of any of the five clinical groups of AD development.
The guide provides examples of how Transcreener allowed rapid assay development to enable screening for kinases in innate immune pathways.
The ML algorithm explores how genetic mutations collectively influence a tumour’s reaction to drugs impeding DNA replication.
New software can make protein molecules that bind with high affinity and specificity to many biomarkers, including human hormones.
A new deep-learning method could enhance therapeutic devices for people with neurological or mental health conditions.
Researchers, using high-resolution mapping and mathematical modelling, have found mechanisms controlling mutation-driven diseases.
An advanced computational model enables scientists to study how cancer cells navigate through blood vessels.
Combining cancerous and non-cancerous cell patterns, the AI model evaluates breast cancer outcomes better than expert pathologists.
Researchers have developed an AI based model that is 80 percent accurate in predicting the therapy outcome of high-grade ovarian cancer.
Percent necrosis calculated with machine learning model for patients with osteosarcoma provides an accurate prognosis for survival.