Medical Ethics / Professional Responsibility

HyperBind2: Multi-Shot Learning Enables Progressive Improvement in Computational Antibody Discovery

Antibody discovery remains constrained by resource-intensive experimental screening approaches that offer limited control over critical properties. Here we present HyperBind2, a machine learning platform that progressively improves antibody-antigen interaction predictions through experimental feedback cycles. Unlike static or zero-shot computational approaches, HyperBind2 employs multi-shot learni...

Privacy-preserving AUC Computation in Distributed Machine Learning with PHT-meDIC

Ensuring privacy in distributed machine learning while computing the Area Under the Curve (AUC) is a significant challenge because pooling sensitive test data is often not allowed. Although cryptographic methods can address some of these concerns, they may compromise either scalability or accuracy. In this paper, we present two privacy-preserving solutions for secure AUC computation across multipl...

Designing AI-powered healthcare assistants to effectively reach vulnerable populations with health care services: A discrete choice experiment among South African university students

South African young adults are at increased risk for HIV acquisition and other non-communicable diseases and face significant barriers to accessing he...

Artificial Intelligence in Medicine: Revolutionizing Healthcare Practices and Patient Outcomes

Artificial intelligence (AI) has transformed medicine, advancing diagnostics, treatment, and patient outcomes. This study employs bibliometric analysi...

Benchmarking transformer-based models for medical record deidentification: A single centre, multi-specialty evaluation

Robust de-identification is necessary to preserve patient confidentiality and maintain public acceptance of electronic health record (EHR) research. M...

Exploring Healthcare Professionals’ Perspectives on Artificial Intelligence in Palliative Care: A Qualitative Study

The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routin...

Secure and Efficient Federated Learning for Predictive Modeling in Resource-Constrained Healthcare Systems

Predictive modeling in healthcare holds promise for improving clinical outcomes, but in many low-resource settings, data fragmentation, privacy concer...

Privacy-Preserving Retrieval-Augmented Generation on Local Devices for Regenerative Medicine Applications

Retrieval-augmented generation (RAG) has emerged as a promising approach to improve the factual consistency and domain-specific accuracy of large lang...

Deep learning enables fully automated cineCT-based assessment of regional right ventricular function

Right ventricular (RV) function is a key factor in the diagnosis and prognosis of heart disease. However, current advanced CT-based assessments rely o...

Decentralized, privacy-preserving surgical video analysis with Swarm Learning

Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than p...

Sociodemographic Bias in Large Language Model Clinical Trial Screening

Large language models (LLMs) are increasingly used in randomized clinical trial (RCT) screening, but their potential for sociodemographic bias remains...

Evaluating the acceptability, usability and clinical appropriateness of Your Path, an AI-powered tool facilitating relevant access to HIV services post-HIV self-testing in South Africa

Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HIVST offers p...

Physical Activity Shapes Brain Structure, Function, and the Computational Mechanisms of Cognitive Control

Sedentarism is prevalent and associated with poorer mental and physical health. Whether everyday physical activity (PA) maps onto computational decisi...

FGAseg: Fine-Grained Pixel-Text Alignment for Open-Vocabulary Semantic Segmentation

Open-vocabulary segmentation aims to identify and segment specific regions and objects based on text-based descriptions. A common solution is to lev...

A Survey of Secure Semantic Communications

Semantic communication (SemCom) is regarded as a promising and revolutionary technology in 6G, aiming to transcend the constraints of ``Shannon's tr...

DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation.

Medical image segmentation plays a crucial role in computer-aided diagnosis. By segmenting pathological tissues in medical images, doctors can observe...

Enhancing Privacy-Preserving Cancer Classification with Convolutional Neural Networks.

Precision medicine significantly enhances patients prognosis, offering personalized treatments. Particularly for metastatic cancer, incorporating prim...

HCAP: Hybrid cyber attack prediction model for securing healthcare applications.

The rapid development and integration of interconnected healthcare devices and communication networks within the Internet of Medical Things (IoMT) hav...

Exploiting Boundary Loss for the Hierarchical Panoptic Segmentation of Plants and Leaves

Precision agriculture leverages data and machine learning so that farmers can monitor their crops and target interventions precisely. This enables t...

B2Net: Camouflaged Object Detection via Boundary Aware and Boundary Fusion

Camouflaged object detection (COD) aims to identify objects in images that are well hidden in the environment due to their high similarity to the ba...