AIMC Topic: Neural Networks, Computer

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Automated detection of myocardial infarction based on an improved state refinement module for LSTM/GRU.

Artificial intelligence in medicine
Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary arteries. The visual inspection of electrocardiogram (ECG) is the main diagnosis pattern, while it is taxing and time-consuming. Motivated from state re...

Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

Accident; analysis and prevention
To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a n...

Enhancing fracture diagnosis in pelvic X-rays by deep convolutional neural network with synthesized images from 3D-CT.

Scientific reports
Pelvic fractures pose significant challenges in medical diagnosis due to the complex structure of the pelvic bones. Timely diagnosis of pelvic fractures is critical to reduce complications and mortality rates. While computed tomography (CT) is highly...

A probabilistic knowledge graph for target identification.

PLoS computational biology
Early identification of safe and efficacious disease targets is crucial to alleviating the tremendous cost of drug discovery projects. However, existing experimental methods for identifying new targets are generally labor-intensive and failure-prone....

Amino-functionalized novel biosorbent for effective removal of fluoride from water: process optimization using artificial neural network and mechanistic insights.

Environmental science and pollution research international
Aqueous fluoride ( ) pollution is a global threat to potable water security. The present research envisions the development of novel adsorbents from indigenous Limonia acidissima L. (fruit pericarp) for effective aqueous defluoridation. The adsorben...

Are deep learning classification results obtained on CT scans fair and interpretable?

Physical and engineering sciences in medicine
Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep...

Evaluation of large language models performance against humans for summarizing MRI knee radiology reports: A feasibility study.

International journal of medical informatics
OBJECTIVES: This study addresses the critical need for accurate summarization in radiology by comparing various Large Language Model (LLM)-based approaches for automatic summary generation. With the increasing volume of patient information, accuratel...

Investigation of out-of-distribution detection across various models and training methodologies.

Neural networks : the official journal of the International Neural Network Society
Machine learning-based algorithms demonstrate impressive performance across numerous fields; however, they continue to suffer from certain limitations. Even sophisticated and precise algorithms often make erroneous predictions when implemented with d...

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Computational biology and chemistry
Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable clues for in-depth exploration of molecular-level biological processes. Protein-protein docking tech...

Registration of multimodal bone images based on edge similarity metaheuristic.

Computers in biology and medicine
OBJECTIVE: Blurry medical images affect the accuracy and efficiency of multimodal image registration, whose existing methods require further improvement.