AI Medical Compendium Journal:
International journal of medical informatics

Showing 101 to 110 of 372 articles

Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses.

International journal of medical informatics
BACKGROUND: Breast cancer is the most common cancer diagnosed in women globally. Online cancer communities (OCCs) provide platforms for breast cancer patients to connect, share experiences, and support each other. These communities facilitate discuss...

Enhanced NSCLC subtyping and staging through attention-augmented multi-task deep learning: A novel diagnostic tool.

International journal of medical informatics
OBJECTIVES: The objective of this study is to develop a novel multi-task learning approach with attention encoders for classifying histologic subtypes and clinical stages of non-small cell lung cancer (NSCLC), with superior performance compared to cu...

Decoding the black box: Explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the art systematic review.

International journal of medical informatics
OBJECTIVE: Explainable Artificial Intelligence (XAI) is increasingly recognized as a crucial tool in cancer care, with significant potential to enhance diagnosis, prognosis, and treatment planning. However, the holistic integration of XAI across all ...

Accuracy of machine learning in diagnosing microsatellite instability in gastric cancer: A systematic review and meta-analysis.

International journal of medical informatics
BACKGROUND: Significant challenges persist in the early identification of microsatellite instability (MSI) within current clinical practice. In recent years, with the growing utilization of machine learning (ML) in the diagnosis and management of gas...

Expert opinion elicitation for assisting deep learning based Lyme disease classifier with patient data.

International journal of medical informatics
BACKGROUND: Diagnosing erythema migrans (EM) skin lesion, the most common early symptom of Lyme disease, using deep learning techniques can be effective to prevent long-term complications. Existing works on deep learning based EM recognition only uti...

CrossViT with ECAP: Enhanced deep learning for jaw lesion classification.

International journal of medical informatics
BACKGROUND: Radiolucent jaw lesions like ameloblastoma (AM), dentigerous cyst (DC), odontogenic keratocyst (OKC), and radicular cyst (RC) often share similar characteristics, making diagnosis challenging. In 2021, CrossViT, a novel deep learning appr...

Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis.

International journal of medical informatics
BACKGROUND: Early and reliable prognostication in post-cardiac arrest patients remains challenging, with various factors linked to return of spontaneous circulation (ROSC), survival, and neurological results. Machine learning and deep learning models...

Evaluating the Effectiveness of advanced large language models in medical Knowledge: A Comparative study using Japanese national medical examination.

International journal of medical informatics
UNLABELLED: Study aims and objectives. This study aims to evaluate the accuracy of medical knowledge in the most advanced LLMs (GPT-4o, GPT-4, Gemini 1.5 Pro, and Claude 3 Opus) as of 2024. It is the first to evaluate these LLMs using a non-English m...

Machine learning models to further identify advantaged populations that can achieve functional cure of chronic hepatitis B virus infection after receiving Peg-IFN alpha treatment.

International journal of medical informatics
OBJECTIVE: Functional cure is currently the highest goal of hepatitis B virus(HBV) treatment.Pegylated interferon(Peg-IFN) alpha is an important drug for this purpose,but even in the hepatitis B e antigen(HBeAg)-negative population,there is still a p...

OrthoMortPred: Predicting one-year mortality following orthopedic hospitalization.

International journal of medical informatics
OBJECTIVE: Predicting mortality risk following orthopedic surgery is crucial for informed decision-making and patient care. This study aims to develop and validate a machine learning model for predicting one-year mortality risk after orthopedic hospi...