AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Data Analysis

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Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks.

BMC bioinformatics
BACKGROUND: Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are requir...

Retrospective Data Analysis of the Influence of Age and Sex on TPMT Activity and Its Phenotype-Genotype Correlation.

The journal of applied laboratory medicine
BACKGROUND: Therapeutic efficacy and toxicity of thiopurine drugs (used as anticancer and immunosuppressant agents) are affected by thiopurine S-methyltransferase (TPMT) enzyme activity. genotype and/or phenotype is used to predict the risk for adve...

Imbalanced biomedical data classification using self-adaptive multilayer ELM combined with dynamic GAN.

Biomedical engineering online
BACKGROUND: Imbalanced data classification is an inevitable problem in medical intelligent diagnosis. Most of real-world biomedical datasets are usually along with limited samples and high-dimensional feature. This seriously affects the classificatio...

Machine learning in critical care: state-of-the-art and a sepsis case study.

Biomedical engineering online
BACKGROUND: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This challenge entails the dauntin...

A dataset of clinically generated visual questions and answers about radiology images.

Scientific data
Radiology images are an essential part of clinical decision making and population screening, e.g., for cancer. Automated systems could help clinicians cope with large amounts of images by answering questions about the image contents. An emerging area...

Computational prediction of inter-species relationships through omics data analysis and machine learning.

BMC bioinformatics
BACKGROUND: Antibiotic resistance and its rapid dissemination around the world threaten the efficacy of currently-used medical treatments and call for novel, innovative approaches to manage multi-drug resistant infections. Phage therapy, i.e., the us...

Internet of instruments: Connectivity of research instruments and artificial intelligence could drastically advance experimental science.

EMBO reports
The internet of things is arriving at the laboratory, connecting instruments for remote control and monitoring. Along with Artificial Intelligence Software to analyse data and design experiments, it could fundamentally change the way research is done...

SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes.

BMC bioinformatics
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ont...

A data-driven artificial intelligence model for remote triage in the prehospital environment.

PloS one
In a mass casualty incident, the factors that determine the survival rate of injured patients are diverse, but one of the key factors is the time for triage. Additionally, the main factor that determines the time of triage is the number of medical pe...

Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors.

Sensors (Basel, Switzerland)
Near-infrared (NIR) spectral sensors deliver the spectral response of the light absorbed by materials for quantification, qualification or identification. Spectral analysis technology based on the NIR sensor has been a useful tool for complex informa...