AIMC Topic: Humans

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Causal relationship extraction from biomedical text using deep neural models: A comprehensive survey.

Journal of biomedical informatics
The identification of causal relationships between events or entities within biomedical texts is of great importance for creating scientific knowledge bases and is also a fundamental natural language processing (NLP) task. A causal (cause-effect) rel...

Can methods of artificial intelligence aid in optimizing patient selection in patients undergoing intrauterine inseminations?

Journal of assisted reproduction and genetics
PURPOSE: AI and its machine learning algorithms have proven useful in several fields of medicine, including medically assisted reproduction. The purpose of the study was to construct several predictive models based on clinical data and select the bes...

A deep learning-based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images.

Medical physics
PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, which is recognized as accumulation of plaques in arterial wall tissues. Optical Coherence Tomography (OCT) is a light-based imaging system used in cardio...

DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization.

Journal of chemical information and modeling
Lead optimization, a critical step in early stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve properties such as binding affinity. We recently developed DeepFrag, a deep-learning model capable of recom...

Enhanced facial expression recognition using 3D point sets and geometric deep learning.

Medical & biological engineering & computing
Facial expression recognition plays an essential role in human conversation and human-computer interaction. Previous research studies have recognized facial expressions mainly based on 2D image processing requiring sensitive feature engineering and c...

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.

International journal of environmental research and public health
Few studies have been conducted to classify and predict the influence of nutritional intake on overweight/obesity, dyslipidemia, hypertension and type 2 diabetes mellitus (T2DM) based on deep learning such as deep neural network (DNN). The present st...

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.

International journal of molecular sciences
Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fields like drug design and development. Most promoters contain a number of transcription factor (TF) binding sites, but only a small minority has been id...

DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method.

International journal of molecular sciences
It is essential for future research to develop a new, reliable prediction method of DNA binding sites because DNA binding sites on DNA-binding proteins provide critical clues about protein function and drug discovery. However, the current prediction ...

COVID-19 diagnosis by routine blood tests using machine learning.

Scientific reports
Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that ...