AIMC Topic: Machine Learning

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ActiMut-XGB: Predicting thermodynamic stability of point mutations for CALB with protein language model.

International journal of biological macromolecules
Predicting the functional impact of single-point mutations on protein residual activity, especially after high-temperature incubation, is critical in protein engineering. We present an innovative machine learning model based on eXtreme Gradient Boost...

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Surgical pathology clinics
Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to support the diagnosis and classification of pathology specimens. These tools rely on digitization of pathology glass slides as whole slide images, allowi...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may allow for real-time modifications based on emergi...

Learning to utilize internal protein 3D nanoenvironment descriptors in predicting CRISPR-Cas9 off-target activity.

NAR genomics and bioinformatics
Despite advances in determining the factors influencing cleavage activity of a CRISPR-Cas9 single guide RNA (sgRNA) at an (off-)target DNA sequence, a comprehensive assessment of pertinent physico-chemical/structural descriptors is missing. In partic...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Hospital pediatrics
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...

Ceasing sampling at wastewater treatment plants where viral dynamics are most predictable.

Epidemics
Wastewater sampling has been shown to be an effective tool for monitoring the dynamics of an infectious disease. During the COVID-19 pandemic, many sampling sites were opened in order to capture as much information as possible. However, with the pand...

Large-scale plasma proteomic profiling unveils diagnostic biomarkers and pathways for Alzheimer's disease.

Nature aging
Proteomic studies have been instrumental in identifying brain, cerebrospinal fluid and plasma proteins associated with Alzheimer's disease (AD). Here, we comprehensively examined 6,905 aptamers corresponding to 6,106 unique proteins in plasma in more...

Research on the influencing factors of PM in China at different spatial scales based on machine learning algorithm.

Environment international
PM pollution is one of the prominent environmental issues currently faced in China, influenced by various factors and showed significant spatial differences. In this study, the Light Gradient Boosting Machine (LightGBM) model was employed in combinat...

Exploring the morpho-tectonic nature, hydrological and physical characteristics of a watershed and prioritizing sub-watersheds surface runoff potentialities by integrating MCDM and ensemble machine learning models.

Journal of environmental management
Much effective rainfall often leads to natural and human-induced hazards when unused. Therefore, monitoring and managing water resources by assessing comprehensive surface runoff (SR) potential is crucial instead of relying on broad sub-watershed (SW...

Predicted and Explained: Transforming drug discovery with AI for high-precision receptor-ligand interaction modeling and binding analysis.

Computers in biology and medicine
The pharmaceutical industry faces persistent challenges in developing effective treatments for complex diseases, creating an urgent need for innovative approaches to accelerate drug discovery. A pivotal factor in this process is the accurate predicti...