AIMC Topic: Algorithms

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Deep reinforcement learning-based multi-lane mixed traffic ramp merging strategy.

PloS one
Due to concentrated conflicts, on-ramp merging is an important scenario in the study of new hybrid traffic control. Current research mainly focuses on optimizing the vehicle passage sequence of ramp vehicles merging with mainline vehicles in single-l...

From biosensing to perception: Collaborative few-shot learning for explainable digital biomarker identification in high-dimensional biomedical spectra.

Biosensors & bioelectronics
The application of in vitro diagnostic biosensors for early cancer detection remains challenging due to the insufficient representation by a few molecular biomarkers. Digital biomarkers promise comprehensive disease phenotyping but face constraints o...

Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies.

Proceedings of the National Academy of Sciences of the United States of America
The use of AI, or more generally data-driven algorithms, has become ubiquitous in today's society. Yet, in many cases and especially when stakes are high, humans still make final decisions. The critical question, therefore, is whether AI helps humans...

A comprehensive benchmarking of adaptive sampling tools for nanopore sequencing.

Genome biology
BACKGROUND: Adaptive sampling is an emerging technology to enrich target reads while depleting unwanted reads during real-time nanopore sequencing. The application of different algorithms has spawned various tools for the determination of read reject...

Comparative evaluation of deep learning and traditional models for predicting traffic accident severity in Saudi Arabia.

Scientific reports
Road traffic accidents are one of the leading death causes around the globe, claiming millions of lives every year. Predicting traffic accident severity is essential for road users' safety and accident prevention. Artificial neural network (ANN), Boo...

DBCM-net:dual backbone cascaded multi-convolutional segmentation network for medical image segmentation.

Biomedical physics & engineering express
Medical image segmentation plays a vital role in diagnosis, treatment planning, and disease monitoring. However, endoscopic and dermoscopic images often exhibit blurred boundaries and low contrast, presenting a significant challenge for precise segme...

Machine learning in sex estimation using CBCT morphometric measurements of canines.

Clinical oral investigations
OBJECTIVE: The aim of this study was to assess measurements of the maxillary canines using Cone Beam Computed Tomography (CBCT) and develop a machine learning model for sex estimation.

An improved artificial gorilla troops optimizer for BP neural network-based housing price prediction.

PloS one
In the context of global economic austerity in the post epidemic era, housing, as one of the basic human needs, has become particularly important for accurate prediction of house prices. BP neural network is widely used in prediction tasks, but their...

Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Gestational diabetes mellitus (GDM) affects over 5% of pregnancies worldwide, elevating risks of type 2 diabetes post partum and complications such as fetal death, miscarriage, and congenital abnormalities. Effective GDM management is ess...

Novel and optimized mouse behavior enabled by fully autonomous HABITS: Home-cage assisted behavioral innovation and testing system.

eLife
Mice are among the most prevalent animal models used in neuroscience, benefiting from the extensive physiological, imaging, and genetic tools available to study their brain. However, the development of novel and optimized behavioral paradigms for mic...