Public Health & Policy

Ethics

Latest AI and machine learning research in ethics for healthcare professionals.

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Showing 1975-1995 of 2,862 articles
Non-Invasive Tumor Budding Evaluation and Correlation with Treatment Response in Bladder Cancer: A Multi-Center Cohort Study.

The clinical benefits of neoadjuvant chemoimmunotherapy (NACI) are demonstrated in patients with bla...

NFR-EDL: Non-linear fuzzy rank-based ensemble deep learning for accurate diagnosis of oral and dental diseases using RGB color photography.

BACKGROUND: Oral health plays a vital role in our daily lives, affecting essential activities like e...

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized cl...

Enhanced non-invasive machine learning approach for early colorectal cancer detection: Predictive modeling and validation in a Jordanian cohort.

BACKGROUND: Colorectal cancer (CRC) ranks as the third most prevalent cancer worldwide, posing signi...

Atten-Nonlocal Unet: Attention and Non-local Unet for medical image segmentation.

The convolutional neural network(CNN)-based models have emerged as the predominant approach for medi...

Non-invasive diagnosis of lung diseases via multimodal feature extraction from breathing audio and chest dynamics.

Early and accurate diagnosis of lung diseases is crucial for effective treatment. While traditional ...

Accuracy of robot and template systems in implant cases: A retrospective non-randomized controlled study.

OBJECTIVES: This clinical study aimed to compare the accuracy of implant placement obtained using a ...

A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG.

BACKGROUND AND OBJECTIVE: The aim of this study is to extract a patient-specific viscosity equation ...

GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration.

The registration of coronary artery structures from preoperative coronary computed tomography angiog...

The ethics of autonomous neurosurgical robots (ANRs).

It may only be a handful of years before fully autonomous neurosurgical robots (ANRs) are pushed int...

AI assistance improves people's ability to distinguish correct from incorrect eyewitness lineup identifications.

Mistaken eyewitness identification is one of the leading causes of false convictions. Improving law ...

Classifying athletes and non-athletes by differences in spontaneous brain activity: a machine learning and fMRI study.

Different types of sports training can induce distinct changes in brain activity and function; howev...

Large-Scale Non-Adiabatic Dynamics Simulation Based on Machine Learning Hamiltonian and Force Field: The Case of Charge Transport in Monolayer MoS.

We present an efficient and reliable large-scale non-adiabatic dynamics simulation method based on m...

A Chemistry-Informed Generative Deep Learning Approach for Enhancing Voltammetric Neurochemical Sensing in Living Mouse Brain.

Exploring the time-resolved dynamics of neurochemicals is essential for deciphering neuronal functio...

Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer.

Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patien...

Deep Reinforcement Learning for CT-Based Non-Invasive Prediction of SOX9 Expression in Hepatocellular Carcinoma.

The transcription factor SOX9 plays a critical role in various diseases, including hepatocellular c...

Biology-Informed Matrix Factorization: An AI-Driven Framework for Enhanced Drug Repositioning.

Advances in artificial intelligence (AI) and intelligent computing have significantly accelerated dr...

Mapping Ethical Guidelines for AI in Healthcare: A Global Perspective.

The integration of AI into healthcare has raised ethical concerns, including algorithmic bias, patie...

Exploring Data Science Students' Engagement, Usage Patterns, and Perceptions of Large Language Models in Programming.

Large Language Models (LLMs) are a type of artificial intelligence (AI) that have emerged as powerfu...

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