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2 articles from the last 90 days matching "Deep Learning"

ResearchBIORXIVMay 4

Preprint: Deep learning-based stratification of Schizophrenia Spectrum Disorder from real-world data reveals distinct profiles of common and rare variant genetic signal

Researchers studied over 22,000 people from Denmark to understand why schizophrenia affects people differently. They used artificial intelligence to find ten distinct groups within schizophrenia spectrum disorder based on clinical symptoms and genetic information. This discovery suggests that schizophrenia isn't one single disease but rather multiple related conditions with different genetic causes.

WHY IT MATTERSIf schizophrenia spectrum disorder can be divided into genetically distinct subtypes, future treatments could be personalized to match each person's specific genetic profile rather than using one-size-fits-all approaches.
ℹ Good to knowSchizophrenia Spectrum Disorder
ResearchBIORXIVApr 17

Preprint: The results of Transcriptome-wide Mendelian Randomization (TWMR) in large-scale populations can directly validate, across scales, the results of causal inference from deep learning combined with double machine learning on single-cell transcriptomes of human samples.

Scientists are testing a new way to understand how genes cause diseases by combining two different research methods: one that studies genes in large groups of people, and another that looks at individual cells in the lab. This study checks whether both methods give the same answers, which would help researchers trust their findings more and move treatments from the lab to real patients faster.

WHY IT MATTERSIf validated, this approach could accelerate how researchers identify disease-causing genes in rheumatologic conditions, potentially leading to faster development of targeted treatments for patients with autoimmune and inflammatory diseases.
ℹ Good to know

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