AIMC Topic: Machine Learning

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Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.

Scientific reports
High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data and to the availability of dynamic models that link phenomena across levels: from gene...

Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings.

Scientific reports
Several artificial intelligence algorithms have been proposed to help diagnose glaucoma by analyzing the functional and/or structural changes in the eye. These algorithms require carefully curated datasets with access to ocular images. In the current...

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

Scientific data
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in comp...

A Stock Selection Model of Image Classification Method Based on Convolutional Neural Network.

Computational intelligence and neuroscience
With the development of artificial intelligence technology, an increasing number of researchers try to apply different machine learning and deep learning methods to quantitative trading fields to obtain more stable and efficient trading models. As a ...

Machine Learning for The Prediction of Ranked Applicants and Matriculants to an Internal Medicine Residency Program.

Teaching and learning in medicine
: Residency programs throughout the country each receive hundreds to thousands of applications every year. Holistic review of this many applications is challenging, and to-date, few tools exist to streamline or assist in the process for selecting can...

A Surgeon's Guide to Artificial Intelligence-Driven Predictive Models.

The American surgeon
Artificial intelligence (AI) focuses on processing and interpreting complex information as well as identifying relationships and patterns among complex data. Artificial intelligence- and machine learning (ML)-driven predictions have shown promising p...

Pressure Injury Prediction Model Using Advanced Analytics for At-Risk Hospitalized Patients.

Journal of patient safety
OBJECTIVE: Analyzing pressure injury (PI) risk factors is complex because of multiplicity of associated factors and the multidimensional nature of this injury. The main objective of this study was to identify patients at risk of developing PI.

Scanner model classification with characteristic brightness variations.

Journal of forensic sciences
Analog documents and scanned digitized files are now considered equivalent in legal contexts, and the widespread supply of multi-functional printers has led to a surge in the use of scanned documents. With image editing tools, there has been more cas...

An Ensemble Structure and Physicochemical (SPOC) Descriptor for Machine-Learning Prediction of Chemical Reaction and Molecular Properties.

Chemphyschem : a European journal of chemical physics and physical chemistry
Feature representations, or descriptors, are machines' chemical language that largely shapes the prediction capability, generalizability and interpretability of machine learning models. To develop a generally applicable descriptor is highly warranted...

A Human-Centered Machine-Learning Approach for Muscle-Tendon Junction Tracking in Ultrasound Images.

IEEE transactions on bio-medical engineering
Biomechanical and clinical gait research observes muscles and tendons in limbs to study their functions and behaviour. Therefore, movements of distinct anatomical landmarks, such as muscle-tendon junctions, are frequently measured. We propose a relia...