AIMC Topic: Machine Learning

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An orchestration learning framework for ultrasound imaging: Prompt-Guided Hyper-Perception and Attention-Matching Downstream Synchronization.

Medical image analysis
Ultrasound imaging is pivotal in clinical diagnostics due to its affordability, portability, safety, real-time capability, and non-invasive nature. It is widely utilized for examining various organs, such as the breast, thyroid, ovary, cardiac, and m...

So You've Got a High AUC, Now What? An Overview of Important Considerations when Bringing Machine-Learning Models from Computer to Bedside.

Medical decision making : an international journal of the Society for Medical Decision Making
Machine-learning (ML) models have the potential to transform health care by enabling more personalized and data-driven clinical decision making. However, their successful implementation in clinical practice requires careful consideration of factors b...

Characterize and explore the dynamic changes in the volatility profiles of sauce-flavor baijiu during different rounds by GC-IMS, GC-MS and GC×GC-MS combined with machine learning.

Food research international (Ottawa, Ont.)
The production process of sauce-flavor baijiu (SFB) involves seven distillations, yielding base baijiu of 7 rounds (RSFB), which are then blended to form the final product. Therefore, the quality of the base baijiu is closely related to the quality o...

Machine-learning modeL based on computed tomography body composition analysis for the estimation of resting energy expenditure: A pilot study.

Clinical nutrition ESPEN
BACKGROUND & AIMS: The assessment of resting energy expenditure (REE) is a challenging task with the current existing methods. The reference method, indirect calorimetry (IC), is not widely available, and other surrogates, such as equations and bioim...

Learning contrast and content representations for synthesizing magnetic resonance image of arbitrary contrast.

Medical image analysis
Magnetic Resonance Imaging (MRI) produces images with different contrasts, providing complementary information for clinical diagnoses and research. However, acquiring a complete set of MRI sequences can be challenging due to limitations such as lengt...

Differentiation of Healthy Ex Vivo Bovine Tissues Using Raman Spectroscopy and Interpretable Machine Learning.

Lasers in surgery and medicine
OBJECTIVES: Integrating machine learning with Raman spectroscopy (RS) shows strong potential for intraoperative guidance in orthopedic procedures, but limited algorithm transparency remains a barrier to clinician trust. This study aims to develop int...

Predicting metabolite-disease associations based on dynamic adaptive feature learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, the association between metabolites and complex human diseases has increasingly been recognized as a major research focus. Traditional wet-lab experiments are considered time-consuming and labor-intensive, w...

Anatomical Considerations for Achieving Optimized Outcomes in Individualized Cochlear Implantation.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
HYPOTHESIS: Machine learning models can assist with the selection of electrode arrays required for optimal insertion angles.

Machine learning algorithms for heart disease diagnosis: A systematic review.

Current problems in cardiology
BACKGROUND: The heart is a vital organ that pumps blood throughout the body. Its proper functioning is crucial for maintaining overall health, and any malfunction can significantly impact other bodily systems. Recently, machine learning has emerged a...

Development of machine learning models for estimation of disintegration time on fast-disintegrating tablets.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The disintegration time for solid dosage oral formulations is directly influenced by diverse factors such as molecular properties, physical characteristics, excipient compositions, and formulation-specific attributes. This research addresses the chal...