AIMC Topic: Middle Aged

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Evaluating the impact of explainable AI on clinicians' decision-making: A study on ICU length of stay prediction.

International journal of medical informatics
BACKGROUND: Explainable Artificial Intelligence (XAI) is increasingly vital in healthcare, where clinicians need to understand and trust AI-generated recommendations. However, the impact of AI model explanations on clinical decision-making remains in...

Can ChatGPT detect breast cancer on mammography?

Journal of medical screening
Some noteworthy studies have questioned the use of ChatGPT, a free artificial intelligence program that has become very popular and widespread in recent times, in different branches of medicine. In this study, the success of ChatGPT in detecting brea...

SMOTE-Enhanced Explainable Artificial Intelligence Model for Predicting Visual Field Progression in Myopic Normal Tension Glaucoma.

Journal of glaucoma
PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension glaucoma. Using SHAP analysis, the key variables driving disease progression were identified.

Initial seizure episodes risk factors identification during hospitalization of ICU patients: A retrospective analysis of the eICU collaborative research database.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: We aimed to identify risk factors for initial seizure episodes in ICU patients using various machine learning algorithms.

Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma.

Journal of proteome research
The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal...

Using the Geriatric Emergency Perioperative Risk Index Derived From Artificial Intelligence Algorithms to Predict Outcomes of Geriatric Emergency General Surgery.

The Journal of surgical research
INTRODUCTION: The objective of this study was to employ artificial intelligence (AI) technology for the development of a model that can accurately forecast the outcome of emergency general surgery (EGS) in elderly patients. Additionally, an innovativ...

Combining Ultrasound Imaging and Molecular Testing in a Multimodal Deep Learning Model for Risk Stratification of Indeterminate Thyroid Nodules.

Thyroid : official journal of the American Thyroid Association
Indeterminate cytology (Bethesda III and IV) represents 15-30% of biopsied thyroid nodules and require additional diagnostic testing. Molecular testing (MT) is a commonly used diagnostic tool that evaluatesmalignancy risk through next generation seq...

Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

Nutrients
BACKGROUND/OBJECTIVES: Obesity is a global health issue, and in this context, bariatric surgery is considered the most effective treatment for severe cases. However, postoperative outcomes vary widely among individuals, driving the development of too...

Machine learning models for predicting tibial intramedullary nail length.

BMC musculoskeletal disorders
BACKGROUND: Tibial intramedullary nailing (IMN) represents a standard treatment for fractures of the tibial shaft. Nevertheless, accurately predicting the appropriate nail length prior to surgery remains a challenging endeavour. Conventional techniqu...