AIMC Topic: Reproducibility of Results

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A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective.

JMIR formative research
BACKGROUND: Hepatitis B virus (HBV) can be transmitted from mother to child either through transplacental infection or via blood-to-blood contact during or immediately after delivery. Early and accurate risk assessments are essential for guiding clin...

FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17.

Scientific reports
Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging te...

Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images.

BMC musculoskeletal disorders
OBJECTIVE: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images.

Comparison of ChatGPT and Internet Research for Clinical Research and Decision-Making in Occupational Medicine: Randomized Controlled Trial.

JMIR formative research
BACKGROUND: Artificial intelligence is becoming a part of daily life and the medical field. Generative artificial intelligence models, such as GPT-4 and ChatGPT, are experiencing a surge in popularity due to their enhanced performance and reliability...

Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

BMC oral health
BACKGROUND: This study focused on two Artificial Intelligence chatbots, ChatGPT 3.5 and Google Gemini, as the primary tools for answering questions related to traumatic dental injuries. The aim of this study to evaluate the reliability, understandabi...

Optimized deep residual networks for early detection of myocardial infarction from ECG signals.

BMC cardiovascular disorders
Globally, the high number of deaths are happening due to Myocardial infarction (MI). MI is considered as a life-threatening disease, which leads to an increase number of deaths or damage to the heart, and hence, prompt detection of MI is critical to ...

Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.

African journal of reproductive health
This study built a model to forecast the maturity of lungs by blending radiomics and deep learning methods. We examined ultrasound images from 263 pregnancies in the pregnancy stages. Utilizing the GE VOLUSON E8 system we captured images to extract a...

Classification of internet addiction using machine learning on electroencephalography synchronization and functional connectivity.

Psychological medicine
BACKGROUND: Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment a...

A Mixed-Methods Evaluation of LLM-Based Chatbots for Menopause.

Studies in health technology and informatics
The integration of Large Language Models (LLMs) into healthcare settings has gained significant attention, particularly for question-answering tasks. Given the high-stakes nature of healthcare, it is essential to ensure that LLM-generated content is ...

Large Language Model-Assisted Systematic Review: Validation Based on Cochrane Review Data.

Studies in health technology and informatics
Large Language Models (LLMs) offer potential for automating systematic reviews, a labor-intensive process in evidence-based medicine. We evaluated GPT-4o, GPT-4o-mini, and Llama 3.1:8B on abstract screening and risk of bias assessment using 12 Cochra...