AIMC Topic: Machine Learning

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LMProtein: a protein language model based framework for protein structural property prediction.

Physical chemistry chemical physics : PCCP
Recent advances in machine learning and self-supervised deep language modeling have made it possible to accurately predict protein structural properties. Most existing models and pretraining methods leverage evolutionary information in multiple seque...

AI assisted triage of UK patients in mental health care services: a qualitative focus group study of patients' attitudes.

BMC psychiatry
BACKGROUND: The referral process between healthcare services can be complex, especially in psychiatry, leading to significant delays and 'hidden waiting lists'. Digital approaches may be helpful. The CHRONOSIG (CHRONOlogical SIGnature) project aims t...

Climate and traits drive bark decomposition patterns at global scale.

Nature communications
Tree bark represents a large global carbon stock, comprising 2-20 % of woody biomass, and plays a distinct role in carbon and nutrient cycling. It is poorly understood how different abiotic and biotic drivers contribute to bark decomposition globally...

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.

JMIR cancer
BACKGROUND: Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular feat...

Neutrophil Percentage-to-Albumin Ratio as a Novel Prognostic Biomarker in Adult Diffuse Gliomas: Retrospective Study Integrating 3 Machine Learning Models and Cox Regression.

JMIR medical informatics
BACKGROUND: Adult-type diffuse glioma (ADG) is the most common primary malignant tumor of the central nervous system. Its highly invasive nature, marked heterogeneity, and resistance to therapy contribute to a high risk of recurrence and poor prognos...

Early diagnostic biomarkers for acute myocardial infarction unveiled by metabolomics, Mendelian randomization, and machine learning.

Molecular biomedicine
Acute myocardial infarction (AMI) remains a leading cause of global cardiovascular morbidity and mortality. Limitations in current diagnostic methods hinder early detection and intervention, creating an urgent need for novel early diagnostic biomarke...

Fishes Go MOO: Pareto analysis of speed and cost of transport across a 6-dimensional design space.

Bioinspiration & biomimetics
Aquatic organisms exhibit remarkable diversity in swimming strategies, even within shared modes such as body-caudal fin (BCF) propulsion. Here, we investigate the biomechanical underpinnings of BCF swimming by mapping performance trade-offs across a ...

Computational design of protein complexes: influence of binding affinity.

Chemical communications (Cambridge, England)
The interaction of proteins with diverse molecular partners, including other proteins, nucleic acids, and carbohydrates, is essential for performing various functions, from signal transduction and gene regulation to immune recognition and cellular tr...

Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.

Journal of neurointerventional surgery
BACKGROUND: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction a...

Predicting the effect of CRISPR-Cas9-based epigenome editing.

eLife
Epigenetic regulation orchestrates mammalian transcription, but functional links between them remain elusive. To tackle this problem, we use epigenomic and transcriptomic data from 13 ENCODE cell types to train machine learning models to predict gene...