AIMC Topic: Machine Learning

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Harnessing AI for precision medicine and its applications in genomics, systems pharmacology, and drug discovery.

European journal of pharmacology
Artificial intelligence and machine learning are revolutionizing pharmaceutical research by enabling the rapid analysis of complex datasets and automating critical tasks throughout the drug-development process. In this review, we surveyed how artific...

Identifying Key Taxa for Algal Blooms in a Large Aquatic Ecosystem through Machine Learning.

Environmental science & technology
Identifying key species responsible for excessive growth of algae communities, as reflected by the floating algae index (FAI), is crucial for developing targeted management strategies to control algal blooms (ABs). However, current approaches for alg...

Enhanced ribbon quality in roller compaction process by mitigating splitting through a machine-learning framework.

International journal of pharmaceutics
Ribbon splitting, a phenomenon that can occur during the roller compaction operation used in dry granulation processes, can lead to compromised granule uniformity, poor tabletability, and ultimately, off-specification tablet production. Despite its i...

Unveiling chemical space, scaffold diversity, critical structural features of pesticides: A comprehensive QSAR, qRASAR, machine learning studies to predict pesticides toxicity.

The Science of the total environment
The increasing use of pesticides in agriculture and urban areas has led to significant contamination of aquatic ecosystems, posing risks to non-target species. Fish, particularly the rainbow trout (Oncorhynchus mykiss), are highly vulnerable due to t...

Mechanism-Driven Features Enable Asn Deamidation Reactivity Prediction via Machine Learning Methods.

Journal of chemical information and modeling
The spontaneous deamidation of Asparagine (Asn) residues is a common post-translational modification of proteins that can occur on disparate time scales, ranging from hours to thousands of years. This variability in the reaction rate reflects the inf...

Drug and Clinical Candidate Drug Data in ChEMBL.

Journal of medicinal chemistry
ChEMBL is a large-scale, open-access, FAIR database of bioactive molecules with drug-like properties. ChEMBL 35 contains 17,500 approved drugs, and drugs that are progressing through the clinical development pipeline. Drug curation has formed an inte...

Maturity Framework for Operationalizing Machine Learning Applications in Health Care: Scoping Review.

Journal of medical Internet research
BACKGROUND: The exponential growth of publications regarding the application of machine learning (ML) tools in medicine highlights the significant potential for ML to revolutionize the field. Despite the multitude of literature surrounding this topic...

Enteral versus parenteral nutrition in auto-HCT: a randomized controlled trial on clinical outcomes and gut microbiome dynamics.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Disruption of the gut microbiome is a common consequence of chemotherapy, linked with detrimental treatment outcomes (e.g. sepsis), especially in haematopoietic stem cell transplant (HCT) recipients. Preclinical data suggest that enteral nutrition (E...

Letter to the editor: interpretable machine learning model predicts 1‑year inguinal hernia risk after robot‑assisted radical prostatectomy.

Journal of robotic surgery
We read with interest the recent article by Yu et al., "Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy" (DOI: 10.1007/s11701-025-02723-5) , which represents an important step in ap...

Adaptive TreeHive: Ensemble of trees for enhancing imbalanced intrusion classification.

PloS one
Imbalanced intrusion classification is a complex and challenging task as there are few number of instances/intrusions generally considered as minority instances/intrusions in the imbalanced intrusion datasets. Data sampling methods such as over-sampl...