AIMC Topic: Algorithms

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Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.

Scientific reports
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...

Use of natural language processing method to identify regional anesthesia from clinical notes.

Regional anesthesia and pain medicine
INTRODUCTION: Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within indi...

An early prediction model for gestational diabetes mellitus created using machine learning algorithms.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

Microscopy research and technique
This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segmentation of brain tumors. The main objective is to reduce the execution time and accurately locate and segment the tumor, including its subareas. The i...

Natural Language Processing and soft data for motor skill assessment: A case study in surgical training simulations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automated surgical skill assessment using kinematic and video data (hard data) sources has been widely adopted in the literature. However, experts' opinions (soft data) in the form of free-text could be an invaluable source ...

Enhancing diagnosis prediction with adaptive disease representation learning.

Artificial intelligence in medicine
Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future based on their historical electronic health records. The time series model can better capture the temporal progression relationship of patient diseases...

Prediction of landfill gases concentration based on Grey Wolf Optimization - Support Vector Regression during landfill excavation process.

Waste management (New York, N.Y.)
In some areas, there is a phenomenon that the landfill is full or even over-capacity with the extension of the service period. With the aging and damage of the protective facilities, this phenomenon may have a more serious impact on the surrounding e...

Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Accident; analysis and prevention
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...

Prediction of clinical risk factors in pregnancy using optimized neural network scheme.

Placenta
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...

AD-VAE: Adversarial Disentangling Variational Autoencoder.

Sensors (Basel, Switzerland)
Face recognition (FR) is a less intrusive biometrics technology with various applications, such as security, surveillance, and access control systems. FR remains challenging, especially when there is only a single image per person as a gallery datase...