AIMC Topic: Machine Learning

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Virtual histopathology methods in medical imaging - a systematic review.

BMC medical imaging
Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, oft...

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data.

BMC bioinformatics
BACKGROUND: The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potenti...

Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.

Scientific reports
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...

Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...

Uncovering the Probiotic Supplement Landscape: Market Offerings, Sales Patterns, and Future Forecasts Using Machine Learning Approach - A Case Study of Montenegro.

Probiotics and antimicrobial proteins
Global increasing awareness about the health benefits of probiotics resulted to explorational growth in probiotic food supplement market. However, in some countries such as Montenegro, specific probiotic supplement regulation and comprehensive market...

Daily stress detection from real-life speeches using acoustic and semantic information.

Ergonomics
Detecting daily stress is of vital importance for workplace safety and health, and natural speech is recommended as one of the main methods of mental stress detection. This study developed machine-learning models for daily stress detection from real-...

The Value of Whole-Volume Radiomics Machine Learning Model Based on Multiparametric MRI in Predicting Triple-Negative Breast Cancer.

Journal of computer assisted tomography
OBJECTIVE: This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coeffici...

Detecting irregularities in randomized controlled trials using machine learning.

Clinical trials (London, England)
BACKGROUND: Over the course of a clinical trial, irregularities may arise in the data. Trialists implement human-intensive, expensive central statistical monitoring procedures to identify and correct these irregularities before the results of the tri...

Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Patient monitors case study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundHealthcare institutions throughout the world rely on medical devices to provide their services reliably and effectively. However, medical devices can, and do sometimes fail. These failures pose significant risk to patients.ObjectiveOne way ...

Advancement of post-market surveillance of medical devices leveraging artificial intelligence: Infusion pumps case study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundAnalysis of data from incident registries such as MAUDE has identified the need to improve surveillance and maintenance strategies for infusion pumps to enhance patient and healthcare staff safety.ObjectiveThe ultimate goal is to enhance in...