AIMC Topic: Machine Learning

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Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity.

Methods in molecular biology (Clifton, N.J.)
Molecular docking enables large-scale prediction of whether and how small molecules bind to a macromolecular target. Machine-learning scoring functions are particularly well suited to predict the strength of this interaction. Here we describe how to ...

Blood Brain Barrier Permeability Prediction Using Machine Learning Techniques: An Update.

Current pharmaceutical biotechnology
Blood Brain Barrier (BBB) is the collection of vessels of blood with special properties of permeability that allow a limited range of drug and compounds to pass through it. The BBB plays a vital role in maintaining balance between intracellular and e...

Real-time Epidemic Forecasting: Challenges and Opportunities.

Health security
Infectious disease outbreaks play an important role in global morbidity and mortality. Real-time epidemic forecasting provides an opportunity to predict geographic disease spread as well as case counts to better inform public health interventions whe...

Machine Learning: Advanced Image Segmentation Using ilastik.

Methods in molecular biology (Clifton, N.J.)
Segmentation is one of the most ubiquitous problems in biological image analysis. Here we present a machine learning-based solution to it as implemented in the open source ilastik toolkit. We give a broad description of the underlying theory and demo...

A Cell Segmentation/Tracking Tool Based on Machine Learning.

Methods in molecular biology (Clifton, N.J.)
The ability to gain quantifiable, single-cell data from time-lapse microscopy images is dependent upon cell segmentation and tracking. Here, we present a detailed protocol for obtaining quality time-lapse movies and introduce a method to identify (se...

Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.

Molecular imaging
Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital biomarkers within positron emission tomography (PET) imaging have emerged. Interest in the use of artific...

Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

Journal of Alzheimer's disease : JAD
BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investiga...

Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis.

Cancer biomarkers : section A of Disease markers
BACKGROUND: Lung adenocarcinoma (LUAD) accounts for a significant proportion of lung cancer and there have been few diagnostic and therapeutic targets for LUAD due to the lack of specific biomarker. The aim of this study was to identify key long non-...

Benefits, Pitfalls, and Potential Bias in Health Care AI.

North Carolina medical journal
As the health care industry adopts artificial intelligence, machine learning, and other modeling techniques, it is seeing benefits to both patient outcomes and cost reduction; however, it needs to be cognizant of and ensure proper management of the r...

Fuzzy Classification Methods Based Diagnosis of Parkinson's disease from Speech Test Cases.

Current aging science
BACKGROUND: Together with the Alzheimer's disease, Parkinson's disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed or is expected to develo...