AIMC Topic: Machine Learning

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Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data.

Accident; analysis and prevention
Harsh driving events such as harsh brakings (HBs) and harsh accelerations (HAs) are promising Surrogate Safety Measures, already extensively utilised in road safety research. However, their occurrence relative to normal driving conditions has not bee...

Identification of COL3A1 as a candidate protein involved in the crosstalk between obesity and diarrhea using quantitative proteomics and machine learning.

European journal of pharmacology
BACKGROUND: Increasing epidemiologic studies have shown a positive correlation between obesity and chronic diarrhea. Nevertheless, the precise etiology remains uncertain.

High-resolution proteomics and machine-learning identify protein classifiers of honey made by Sicilian black honeybees (Apis mellifera ssp. sicula).

Food research international (Ottawa, Ont.)
Apis mellifera ssp. sicula, also known as the Sicilian black honeybee, is a Slow Food Presidium that produces honey with outstanding nutraceutical properties, including high antioxidant capacity. In this study, we used high-resolution proteomics to p...

UC-Hybrid: Uncertainty-based contrastive learning on hybrid network for medical image segmentation.

Computer methods and programs in biomedicine
Medical image segmentation has made remarkable progress with advances in deep learning technology, depending on the quality and quantity of labeled data. Although various deep learning model structures and training methods have been proposed and high...

Artificial Intelligence and Machine Learning for Inborn Errors of Immunity: Current State and Future Promise.

The journal of allergy and clinical immunology. In practice
Artificial intelligence (AI) and machine learning (ML) research within medicine has exponentially increased over the last decade, with studies showcasing the potential of AI/ML algorithms to improve clinical practice and outcomes. Ongoing research an...

Significance of plasma p-tau217 in predicting long-term dementia risk in older community residents: Insights from machine learning approaches.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Whether plasma biomarkers play roles in predicting incident dementia among the general population is worth exploring.

Artificial intelligence methods available for cancer research.

Frontiers of medicine
Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience...

Smart parallel automated cryo-electron tomography.

Nature methods
In situ cryo-electron tomography enables investigation of macromolecules in their native cellular environment. Samples have become more readily available owing to recent software and hardware advancements. Data collection, however, still requires an ...

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.

The Milbank quarterly
Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our ability to define its boundaries and roles in health care and regulate its application in legal and ethical ways. Significant progress has been made ...