AIMC Topic: Humans

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At-home, telehealth-supported ketamine treatment for depression: Findings from longitudinal, machine learning and symptom network analysis of real-world data.

Journal of affective disorders
BACKGROUND: Improving safe and effective access to ketamine therapy is of high priority given the growing burden of mental illness. Telehealth-supported administration of sublingual ketamine is being explored toward this goal.

Knowledge, attitudes and practices of using Indocyanine Green (ICG) fluorescence in emergency surgery: an international web-based survey in the ARtificial Intelligence in Emergency and trauma Surgery (ARIES)-WSES project.

Updates in surgery
Fluorescence imaging is a real-time intraoperative navigation modality to enhance surgical vision and it can guide emergency surgeons while performing difficult, high-risk surgical procedures. The aim of this study is to assess current knowledge, att...

Empirical validation of Conformal Prediction for trustworthy skin lesions classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-r...

An innovative supervised longitudinal learning procedure of recurrent neural networks with temporal data augmentation: Insights from predicting fetal macrosomia and large-for-gestational age.

Computers in biology and medicine
BACKGROUND: Longitudinal data in health informatics studies often present challenges due to sparse observations from each subject, limiting the application of contemporary deep learning for prediction. This issue is particularly relevant in predictin...

Artificial Intelligence Helps Pathologists Increase Diagnostic Accuracy and Efficiency in the Detection of Breast Cancer Lymph Node Metastases.

The American journal of surgical pathology
The detection of lymph node metastases is essential for breast cancer staging, although it is a tedious and time-consuming task where the sensitivity of pathologists is suboptimal. Artificial intelligence (AI) can help pathologists detect lymph node ...

Recent progress in machine learning approaches for predicting carcinogenicity in drug development.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: This review explores the transformative impact of machine learning (ML) on carcinogenicity prediction within drug development. It discusses the historical context and recent advancements, emphasizing the significance of ML methodologies...

Predicting medical waste generation and associated factors using machine learning in the Kingdom of Bahrain.

Environmental science and pollution research international
Effective planning and managing medical waste necessitate a crucial focus on both the public and private healthcare sectors. This study uses machine learning techniques to estimate medical waste generation and identify associated factors in a represe...