AIMC Topic: Adult

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Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.

Breast cancer research : BCR
BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a MRI-based enhanced self-attention network (MESN) for ...

Deep learning assisted retinal microvasculature assessment and cerebral small vessel disease in Fabry disease.

Orphanet journal of rare diseases
PURPOSE: The aim of this study was to assess retinal microvascular parameters (RMPs) in Fabry disease (FD) using deep learning, and analyze the correlation with brain lesions related to cerebral small vessel disease (CSVD).

An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.

Scientific reports
Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative...

Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient.

Scientific reports
Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on EEG for assessing brain injury, with some exploring...

Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.

Scientific reports
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sou...

Communication challenges and experiences between parents and providers in South Korean paediatric emergency departments: a qualitative study to define AI-assisted communication agents.

BMJ open
OBJECTIVES: This study aimed to explore communication challenges between parents and healthcare providers in paediatric emergency departments (EDs) and to define the roles and functions of an artificial intelligence (AI)-assisted communication agent ...

Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?

Journal of plastic surgery and hand surgery
BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. While we have yet to discover a way to preserve youth eternally, we have made significant progress in understanding the aging process and in developing ph...

Machine learning-based non-invasive continuous dynamic monitoring of human core temperature with wearable dual temperature sensors.

Physiological measurement
Due to the growing demand for personal health monitoring in extreme environments, continuous monitoring of core temperature has become increasingly important. Traditional monitoring methods, such as mercury thermometers and infrared thermometers, may...

Positive relationship between education level and risk perception and behavioral response: A machine learning approach.

PloS one
This paper aims to examine the influence mechanism of education level as a key situational factor in the relationship between risk perception and behavioral response, encompassing both behavioral intention and preparatory behavior. Utilizing non-para...

A machine learning model for prenatal risk prediction of cephalopelvic disproportion-related dystocia: A retrospective study.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To develop a prenatal risk prediction model for cephalopelvic disproportion (CPD)-related dystocia. This model aims to complement obstetricians' empirical judgments by identifying high-risk CPD-related dystocia cases within populations dee...