AIMC Topic: Female

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Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...

Perceptions and attitudes of dental students and dentists in South Korea toward artificial intelligence: a subgroup analysis based on professional seniority.

BMC medical education
BACKGROUND: This study explored dental students' and dentists' perceptions and attitudes toward artificial intelligence (AI) and analyzed differences according to professional seniority.

An ensemble model for predicting dispositions of emergency department patients.

BMC medical informatics and decision making
OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED disposit...

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.

Breast cancer research : BCR
BACKGROUND: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography conside...

Prediction models for postoperative recurrence of non-lactating mastitis based on machine learning.

BMC medical informatics and decision making
OBJECTIVES: This study aims to build a machine learning (ML) model to predict the recurrence probability for postoperative non-lactating mastitis (NLM) by Random Forest (RF) and XGBoost algorithms. It can provide the ability to identify the risk of N...

External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

Scientific reports
A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for au...

Predictive modeling of co-infection in lupus nephritis using multiple machine learning algorithms.

Scientific reports
This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN pati...

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BMJ health & care informatics
BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has...

Home-Based Cognitive Intervention for Healthy Older Adults Through Asking Robots Questions: Randomized Controlled Trial.

JMIR aging
BACKGROUND: Asking questions is common in conversations, and while asking questions, we need to listen carefully to what others say and consider the perspective our questions adopt. However, difficulties persist in verifying the effect of asking ques...

Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels.

Emergency medicine journal : EMJ
BACKGROUND: Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (...