Ethics

Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.

The widespread use of Chat Generative Pre-trained Transformer (known as ChatGPT) and other emerging ...

GEPAF: A non-monotonic generalized activation function in neural network for improving prediction with diverse data distributions characteristics.

The world today has made prescriptive analytics that uses data-driven insights to guide future actio...

A Bioethics Assessment of Continuous Learning in Medicine and AI.

Artificial intelligence and health-related data: The patient's best interest and data ownership dilemma.

The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutioni...

Artificial Intelligence Algorithm Can Predict Lymph Node Malignancy from Endobronchial Ultrasound Transbronchial Needle Aspiration Images for Non-Small Cell Lung Cancer.

INTRODUCTION: Endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) for lung cancer ...

Advanced Non-linear Modeling and Explainable Artificial Intelligence Techniques for Predicting 30-Day Complications in Bariatric Surgery: A Single-Center Study.

PURPOSE: Metabolic bariatric surgery (MBS) became integral to managing severe obesity. Understanding...

An hetero-modal deep learning framework for medical image synthesis applied to contrast and non-contrast MRI.

Some pathologies such as cancer and dementia require multiple imaging modalities to fully diagnose a...

Comparison and benchmark of deep learning methods for non-coding RNA classification.

The involvement of non-coding RNAs in biological processes and diseases has made the exploration of ...

Emotional Labor and the Problem of Exploitation in Roboticized Care Practices: Enriching the Framework of Care Centred Value Sensitive Design.

Care ethics has been advanced as a suitable framework for evaluating the ethical significance of ass...

Multimodal radiomics-based methods using deep learning for prediction of brain metastasis in non-small cell lung cancer withF-FDG PET/CT images.

. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastas...

Identification of neutrophil extracellular trap-related biomarkers in non-alcoholic fatty liver disease through machine learning and single-cell analysis.

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has bec...

Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.

OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with a...

Computer-Simulated Virtual Image Datasets to Train Machine Learning Models for Non-Invasive Fish Detection in Recirculating Aquaculture.

Artificial Intelligence (AI) and Machine Learning (ML) can assist producers to better manage recircu...

The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies.

OBJECTIVE: The incidence of non-melanoma skin cancers, encompassing basal cell carcinoma (BCC) and c...

Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.

AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adv...

Risk factors for depression in China based on machine learning algorithms: A cross-sectional survey of 264,557 non-manual workers.

BACKGROUND: Factors related to depression differ depending on the population studied, and studies fo...

A Physics-Informed Neural Network approach for compartmental epidemiological models.

Compartmental models provide simple and efficient tools to analyze the relevant transmission process...

Towards a configurable and non-hierarchical search space for NAS.

Neural Architecture Search (NAS) outperforms handcrafted Neural Network (NN) design. However, curren...

Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant immunochemotherapy: a multicenter study.

OBJECTIVES: Although neoadjuvant immunochemotherapy has been widely applied in non-small cell lung c...

Early AI Lifecycle Co-Reasoning: Ethics Through Integrated and Diverse Team Science.

Transparency, Evaluation and Going From "Ethics-Washing" to Enforceable Regulation: On Machine Learning-Driven Clinician Decision Aids.