AIMC Topic: Machine Learning

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An Integrated Machine Learning and Remote Sensing Method for Predicting Cyanobacterial Blooms: A Case Study in China's lakes along a large-scale water diversion project.

Environmental management
Cyanobacterial blooms in lakes are a complex and challenging environmental issue worldwide. However, many existing studies on cyanobacterial bloom prediction were constrained by limited data availability, which poses significant challenges to the dev...

Construction and validation of a risk prediction model for complications in patients with acute leukemia based on machine learning.

Scientific reports
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...

Compact machine learning model for perioperative stroke prediction prior to surgery: A retrospective cohort study.

Scientific reports
Perioperative stroke significantly impacts postoperative outcomes. Current risk stratification methods for perioperative stroke prediction lack accuracy and practicality. We aimed to develop a machine learning (ML) model that improves both accuracy a...

Machine learning and bifurcation analysis in a discrete predator-prey model with neem-induced mortality.

Scientific reports
This study develops a discrete-time predator-prey model for guava pest management using the piecewise constant argument (PCA) scheme. The model incorporates logistic prey growth, neem-induced mortality, and predator crowding. Analytical and numerical...

Construction and validation of gene signature for prognosis and drug sensitivity in cholangiocarcinoma based on cellular senescence related genes.

Scientific reports
Cholangiocarcinoma is a very deadly epithelial cell cancer with poor clinical outcome. Cellular senescence plays a vital role in the oncogenesis and the aggressiveness of cholangiocarcinoma. Integrative machine learning procedure including 10 methods...

Association between gut microbiota composition and physical functioning in patients with knee osteoarthritis: a machine learning study.

Scientific reports
Gut dysbiosis and systemic inflammation are increasingly recognized in the pathogenesis of knee osteoarthritis (OA). While altered gut microbiota profiles have been reported, the link between specific microbial taxa and physical functioning in OA pat...

Explainable AI-driven interpretation of environmental drivers of tomato fruit expansion in smart greenhouses using IoT sensing.

Scientific reports
Tomato fruit expansion is a key physiological process that determines fruit size, marketability, and yield, yet its quantitative and threshold-based response to microclimatic factors in smart greenhouses has been insufficiently studied. This study de...

A multimodal physiological dataset for non-invasive blood glucose estimation.

Scientific data
Diabetes is a major health challenge that affects millions of people worldwide. Managing diabetes effectively requires monitoring blood glucose levels continuously, typically through invasive sensing devices such as continuous glucose monitors (CGMs)...

Evaluating machine learning models for clothing size prediction using anthropometric measurements from 3D body scanning.

Scientific reports
An analysis of a dataset comprising 677 participants revealed substantial discrepancies in size categorization. Only 63 individuals (9.15%) maintained consistency across bust, waist, and hip measurements, whereas 614 participants (90.84%) exhibited s...

Bridging the gap: explainable ai for autism diagnosis and parental support with TabPFNMix and SHAP.

Scientific reports
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that affects a growing number of individuals worldwide. Despite extensive research, the underlying causes of ASD remain largely unknown, with genetic predisposition, parental hi...