AIMC Topic: Algorithms

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Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage.

Computational and mathematical methods in medicine
OBJECTIVE: Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid feature convolution neural network to establish the blood pressure model instead of the traditional me...

Finding and understanding pedal misapplication crashes using a deep learning natural language model.

Traffic injury prevention
OBJECTIVE: The objective of this study was to develop a system which used the BERT natural language understanding model to identify pedal misapplication (PM) crashes from their crash narratives and validate the accuracy of the system.

The development of "automated visual evaluation" for cervical cancer screening: The promise and challenges in adapting deep-learning for clinical testing: Interdisciplinary principles of automated visual evaluation in cervical screening.

International journal of cancer
There is limited access to effective cervical cancer screening programs in many resource-limited settings, resulting in continued high cervical cancer burden. Human papillomavirus (HPV) testing is increasingly recognized to be the preferable primary ...

Real-Time Jellyfish Classification and Detection Based on Improved YOLOv3 Algorithm.

Sensors (Basel, Switzerland)
In recent years, jellyfish outbreaks have frequently occurred in offshore areas worldwide, posing a significant threat to the marine fishery, tourism, coastal industry, and personal safety. Effective monitoring of jellyfish is a vital method to solve...

A radiogenomics application for prognostic profiling of endometrial cancer.

Communications biology
Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecul...

Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.

PLoS neglected tropical diseases
BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm sh...

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble.

PLoS computational biology
Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On ...

Research on the Path of Network Opinion Expression in AI Environment for College Students.

Computational and mathematical methods in medicine
Network interaction has evolved into a grouping paradigm as civilization has progressed and artificial intelligence technology has advanced. This network group model has quickly extended communication space, improved communication content, and tailor...

Implementation and Practice of Deep Learning-Based Instance Segmentation Algorithm for Quantification of Hepatic Fibrosis at Whole Slide Level in Sprague-Dawley Rats.

Toxicologic pathology
Exponential development in artificial intelligence or deep learning technology has resulted in more trials to systematically determine the pathological diagnoses using whole slide images (WSIs) in clinical and nonclinical studies. In this study, we a...