Medicolegal

Datasheets for Healthcare AI: A Framework for Transparency and Bias Mitigation

The use of AI in healthcare has the potential to improve patient care, optimize clinical workflows, and enhance decision-making. However, bias, data incompleteness, and inaccuracies in training datasets can lead to unfair outcomes and amplify existing disparities. This research investigates the current state of dataset documentation practices, focusing on their ability to address these challenge...

AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish

Automated fish documentation processes are in the near future expected to play an essential role in sustainable fisheries management and for addressing challenges of overfishing. In this paper, we present a novel and publicly available dataset named AutoFish designed for fine-grained fish analysis. The dataset comprises 1,500 images of 454 specimens of visually similar fish placed in various con...

Regulating algorithmic care in the European Union: evolving doctor-patient models through the Artificial Intelligence Act (AI-Act) and the liability directives.

This article argues that the integration of artificial intelligence (AI) into healthcare, particularly under the European Union's Artificial Intellige...

Deposition Rates in Thermal Laser Epitaxy: Simulation and Experiment

The modeling of deposition rates in Thermal Laser Epitaxy (TLE) is essential for the accurate prediction of the evaporation process and for improved...

Denoising 7T Structural MRI with Conditional Generative Diffusion Models

7T MRI offers ultra-high resolution and improved sensitivity for iron deposition in neurodegenerative disorders, but commonly used acquisitions are lo...

Pharmacological potentiation of Nav1.1 channels in interneurons mitigates tau depositions and neuronal death in a mouse model of neurodegenerative dementias

Epileptiform discharges and neuronal hyperexcitability are key pathophysiological features of Alzheimer’s disease and related tauopathies. We previous...

Neural Network-Enhanced Investigation of Ferroptosis and Druggability in Early-Onset Alzheimer’s Disease

Alzheimer’s disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive dec...

Depositing biological segmentation datasets FAIRly

Segmentation of biological images identifies regions of an image which correspond to specific features of interest, which can be analysed quantitative...

α-SMA/VCAM-1 Dual-Targeted Nanoplatform Improves Drug Release and Therapeutic Efficacy in Liver Fibrosis

Liver fibrosis is a progressive pathological condition characterized by hepatic stellate cell (HSC) activation and vascular endothelial dysfunction, w...

mosna reveals different types of cellular interactions predictive of response to immunotherapies and survival in cancer

Spatially resolved omics enable the discovery of tissue organization of biological or clinical importance. Despite the existence of several methods, p...

Dataset Documentation for Responsible AI: Analysis of Suitability and Usage for Health Datasets

Artificial Intelligence (AI) is rapidly transforming healthcare, but also raising concerns about algorithmic biases that mostly stem from the training...

Biologically Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types

Placenta pathology provides diagnostic insights for understanding pregnancy complications and guides maternal and perinatal care. While placental abno...

AI-based Predictive Signaling Pathway Profiling in Cardiac Fibrosis Suggests a Novel Combinatorial Treatment Strategy

Cardiovascular disease (CVD) remains the leading cause of global mortality, with myocardial fibrosis characterized by excessive extracellular matrix (...

Temporal Dynamics of High-Frequency Oscillations in Alzheimer’s Disease: A Longitudinal Study in hAPP-J20 Mice

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal...

Studying Veteran food insecurity longitudinally using electronic health record data and natural language processing

Food insecurity is an important social risk factor that is directly linked to patient health and well-being. The Department of Veterans Affairs (VA) a...

INSIGHTFUL: Insight Generation through Clinical Annotation, Analysis, and Modeling of Suicide-Related Factors towards Understanding and Lifesaving

Suicide is a critical medical and public health challenge, particularly among individuals with mental illnesses in safety-net hospitals. To uncover in...

Benchmarking And Datasets For Ambient Clinical Documentation: A Scoping Review Of Existing Frameworks And Metrics For AI-Assisted Medical Note Generation

The increasing adoption of ambient artificial intelligence (AI) scribes in healthcare has created an urgent need for robust evaluation frameworks to a...

A Scalable Method for Validated Data Extraction from Electronic Health Records with Large Language Models

Extracting and structuring relevant clinical information from electronic health records (EHRs) remains a challenge due to the heterogeneity of systems...

Evaluation of Machine Learning and Traditional Statistical Models to Assess the Value of Stroke Genetic Liability for Prediction of Risk of Stroke within the UK Biobank

Stroke is one of the leading causes of mortality and long-term disability in adults over 18 years of age globally and its increasing incidence has bec...

A Framework to Assess Clinical Safety and Hallucination Rates of LLMs for Medical Text Summarisation

Integrating large language models (LLMs) into healthcare settings can improve workflow efficiency and patient care by automating tasks such as summari...