AIMC Topic: Machine Learning

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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...

Predicting software reuse using machine learning techniques-A case study on open-source Java software systems.

PloS one
Software reuse is an essential practice to increase efficiency and reduce costs in software production. Software reuse practices range from reusing artifacts, libraries, components, packages, and APIs. Identifying suitable software for reuse requires...

Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder.

PloS one
ELM (Extreme learning machine) has drawn great attention due its high training speed and outstanding generalization performance. To solve the problem that the long training time of kernel ELM auto-encoder and the difficult setting of the weight of ke...

Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.

PloS one
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...

Objectifying aesthetic outcomes following face transplantation - the AI research metrics model (CAARISMA® ARMM).

Journal of stomatology, oral and maxillofacial surgery
BACKGROUND: Face transplantation (FT) offers a reconstructive option for patients with severe facial disfigurements by restoring both function and appearance. Aesthetic outcomes, which are crucial to psychological well-being and social reintegration,...

Identification and understanding of allostery hotspots in proteins: Integration of deep mutational scanning and multi-faceted computational analyses.

Journal of molecular biology
Motivated by recent deep mutational scanning (DMS) experiments, we have carried out a diverse set of computations to better understand the distribution and contributions of allostery hotspot residues in a transcription factor, TetR. These include ext...

Foundations of AI for future physicians: A practical, accessible curriculum.

Medical teacher
WHAT WAS THE EDUCATIONAL CHALLENGE?: The integration of machine learning (ML) and large language models (LLMs) into healthcare is transforming diagnostics, patient care, and administrative workflows. However, most clinicians lack the foundational kno...

Artificial intelligence (AI) in pharmacovigilance: A systematic review on predicting adverse drug reactions (ADR) in hospitalized patients.

Research in social & administrative pharmacy : RSAP
INTRODUCTION: Adverse drug reactions (ADRs) significantly impact healthcare systems, leading to increased hospitalization rates and costs. With the growing adoption of artificial intelligence (AI) in healthcare, machine learning (ML) models offer pro...

Vertical federated learning based on data subset representation for healthcare application.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Artificial intelligence is increasingly essential for disease classification and clinical diagnosis tasks in healthcare. Given the strict privacy needs of healthcare data, Vertical Federated Learning (VFL) has been introduce...

Causal Machine Learning for Left Atrial Appendage Occlusion in Patients With Atrial Fibrillation.

JACC. Clinical electrophysiology
BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to lifelong anticoagulation, but optimal patient selection remains challenging.