AIMC Topic: Machine Learning

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Annotating for Artificial Intelligence Applications in Digital Pathology: A Practical Guide for Pathologists and Researchers.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Training machine learning models for artificial intelligence (AI) applications in pathology often requires extensive annotation by human experts, but there is little guidance on the subject. In this work, we aimed to describe our experience and provi...

Accelerating gradient descent and Adam via fractional gradients.

Neural networks : the official journal of the International Neural Network Society
We propose a class of novel fractional-order optimization algorithms. We define a fractional-order gradient via the Caputo fractional derivatives that generalizes integer-order gradient. We refer it to as the Caputo fractional-based gradient, and dev...

Automated Detection of Aortic Stenosis Using Machine Learning.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Aortic stenosis (AS) is a degenerative valve condition that is underdiagnosed and undertreated. Detection of AS using limited two-dimensional echocardiography could enable screening and improve appropriate referral and treatment of this c...

Perspectives on development of biomedical polymer materials in artificial intelligence age.

Journal of biomaterials applications
Polymer materials are widely used in biomedicine, chemistry and material science, whose traditional preparations are mainly based on experience, intuition and conceptual insight, having been applied to the development of many new materials, but facin...

A tree-based modeling approach for matched case-control studies.

Statistics in medicine
Conditional logistic regression (CLR) is the indisputable standard method for the analysis of matched case-control studies. However, CLR is strongly restricted with respect to the inclusion of non-linear effects and interactions of confounding variab...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

Sensors (Basel, Switzerland)
The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an individual's cardiovascular fitness. A trend is emerging for the development of new machine-learning techniques applied to the automatic process of CPET dat...

Current Advances in Computational Lung Ultrasound Imaging: A Review.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In the field of biomedical imaging, ultrasonography has become common practice, and used as an important auxiliary diagnostic tool with unique advantages, such as being non-ionizing and often portable. This article reviews the state-of-the-art in med...

Model order reduction techniques to identify submarining risk in a simplified human body model.

Computer methods in biomechanics and biomedical engineering
This work investigates linear and non-linear parametric reduced order models (ROM) capable of replacing computationally expensive high-fidelity simulations of human body models (HBM) through a non-intrusive approach. Conventional crash simulation met...

Reinforcement learning in medical image analysis: Concepts, applications, challenges, and future directions.

Journal of applied clinical medical physics
MOTIVATION: Medical image analysis involves a series of tasks used to assist physicians in qualitative and quantitative analyses of lesions or anatomical structures which can significantly improve the accuracy and reliability of medical diagnoses and...

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data.

AAPS PharmSciTech
An increasingly large dataset of pharmaceutics disciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose...