AIMC Topic: Humans

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SCOPE: predicting future diagnoses in office visits using electronic health records.

Scientific reports
We propose an interpretable and scalable model to predict likely diagnoses at an encounter based on past diagnoses and lab results. This model is intended to aid physicians in their interaction with the electronic health records (EHR). To accomplish ...

Beat-wise segmentation of electrocardiogram using adaptive windowing and deep neural network.

Scientific reports
Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a crucial role in many healthcare applications, such as patient monitoring and post treatments. Beat-wise segmentation is one of the essential steps in ensu...

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs.

Nature communications
Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by ...

Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals.

Scientific reports
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a Compact Transformer-based Hand Gestu...

Artificial intelligence in systematic reviews: promising when appropriately used.

BMJ open
BACKGROUND: Systematic reviews provide a structured overview of the available evidence in medical-scientific research. However, due to the increasing medical-scientific research output, it is a time-consuming task to conduct systematic reviews. To ac...

Machine learning to predict environmental dose rates from a radionuclide therapy service - a proof of concept study.

Journal of radiological protection : official journal of the Society for Radiological Protection
The Ionising Radiation Regulations 2017 requires prior risk assessment calculations and regular environmental monitoring of radiation doses. However, the accuracy of prior risk assessments is limited by assumptions and monitoring only provides retros...

Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis.

PLoS computational biology
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygen...

Heart-Brain 346-7 Score: the development and validation of a simple mortality prediction score for carbon monoxide poisoning utilizing deep learning.

Clinical toxicology (Philadelphia, Pa.)
INTRODUCTION: Acute mortality from carbon monoxide poisoning is 1-3%. The long-term mortality risk of survivors of carbon monoxide poisoning is doubled compared to age-matched controls. Cardiac involvement also increases mortality risk. We built a cl...

Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting.

Computational intelligence and neuroscience
The objective of this work was to predict the risk of mortality rate in patients with coronary artery bypass grafting (CABG) based on the risk prediction model of CABG using artificial intelligence (AI) and big data technologies. The clinical data of...