AIMC Topic: Machine Learning

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Using Surgeon Hand Motions to Predict Surgical Maneuvers.

Human factors
OBJECTIVE: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of surgical benchtop simulations.

Machine learning technology in the application of genome analysis: A systematic review.

Gene
Machine learning (ML) is a powerful technique to tackle many problems in data mining and predictive analytics. We believe that ML will be of considerable potentials in the field of bioinformatics since the high-throughput technology is producing ever...

Computer aided diagnosis for suspect keratoconus detection.

Computers in biology and medicine
PURPOSE: To develop a stable and low-cost computer aided diagnosis (CAD) system for early keratoconus detection for clinical use.

An Adaptive Moment estimation method for online AUC maximization.

PloS one
Area Under the ROC Curve (AUC) is a widely used metric for measuring classification performance. It has important theoretical and academic values to develop AUC maximization algorithms. Traditional methods often apply batch learning algorithm to maxi...

Recognition pest by image-based transfer learning.

Journal of the science of food and agriculture
BACKGROUND: Plant pests mainly refers to insects and mites that harm crops and products. There are a wide variety of plant pests, with wide distribution, fast reproduction and large quantity, which directly causes serious losses to crops. Therefore, ...

Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.

Medical image analysis
Good quality of medical images is a prerequisite for the success of subsequent image analysis pipelines. Quality assessment of medical images is therefore an essential activity and for large population studies such as the UK Biobank (UKBB), manual id...

Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation.

Clinical biochemistry
Artificial intelligence (AI) and data science are rapidly developing in healthcare, as is their translation into laboratory medicine. Our review article presents an overview of the data science domain while discussing the reasons for its emergence. W...

Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI.

Neuroradiology
PURPOSE: To evaluate the potential value of machine learning (ML)-based histogram analysis (or first-order texture analysis) on T2-weighted magnetic resonance imaging (MRI) for predicting consistency of pituitary macroadenomas (PMA) and to compare it...

Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Robust and reproducible profiling of cell lines is essential for phenotypic screening assays. The goals of this study were to determine robust and reproducible optical phase signatures of cell lines for classification with machine learning and to cor...

Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.

Journal of proteome research
The large-scale identification of protein-protein interactions (PPIs) between humans and bacteria remains a crucial step in systematically understanding the underlying molecular mechanisms of bacterial infection. Computational prediction approaches a...