Practice Management

Medicolegal

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

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A unified hybrid transformer for joint MRI sequences super-resolution and missing data imputation.

High-resolution multi-modal magnetic resonance imaging (MRI) is crucial in clinical practice for acc...

Artificial Intelligence in Surgical Documentation: A Critical Review of the Role of Large Language Models.

This article provides a critical analysis of the application of the advanced language model, GPT-4, ...

Patient Identification Based on Deep Metric Learning for Preventing Human Errors in Follow-up X-Ray Examinations.

Biological fingerprints extracted from clinical images can be used for patient identity verification...

An Integrated Approach to Improve the Assay Performance of Quantum Dot-Based Lateral Flow Immunoassays by Using Silver Deposition.

Traditional quantum dot-based lateral flow immunoassay (QD-LFIA) is limited to signal loss in part b...

The regulatory environment for artificial intelligence-enabled devices in the United States.

The regulatory environment in the United States has not kept pace with the rapidly developing market...

3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives.

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology w...

msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.

Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and...

ChatGPT in Colorectal Surgery: A Promising Tool or a Passing Fad?

Colorectal surgery is a specialized branch of surgery that involves the diagnosis and treatment of c...

Artificial intelligence tools in clinical neuroradiology: essential medico-legal aspects.

Commercial software based on artificial intelligence (AI) is entering clinical practice in neuroradi...

Artificial Intelligence Applications in Hepatology.

Over the past 2 decades, the field of hepatology has witnessed major developments in diagnostic tool...

Conceptual framework and documentation standards of cystoscopic media content for artificial intelligence.

BACKGROUND: The clinical documentation of cystoscopy includes visual and textual materials. However,...

Standardizing analysis of intra-tumoral heterogeneity with computational pathology.

Many malignant cancers like glioblastoma are highly adaptive diseases that dynamically change their ...

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly ...

Developing a machine learning model to detect diagnostic uncertainty in clinical documentation.

BACKGROUND AND OBJECTIVE: Diagnostic uncertainty, when unrecognized or poorly communicated, can resu...

Artificial Contrast: Deep Learning for Reducing Gadolinium-Based Contrast Agents in Neuroradiology.

Deep learning approaches are playing an ever-increasing role throughout diagnostic medicine, especia...

Investigations into the use of machine learning to predict drug dosage form design to obtain desired release profiles for 3D printed oral medicines.

Three-dimensional (3D) printing, digitalization, and artificial intelligence (AI) are gaining increa...

Recent Advances in the Applications of Additive Manufacturing (3D Printing) in Drug Delivery: A Comprehensive Review.

There has been a tremendous increase in the investigations of three-dimensional (3D) printing for bi...

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.

The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying p...

Artificial intelligence in medicine - is too much transparency a good thing?

Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Comp...

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored wit...

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review.

The growing and aging of the world population have driven the shortage of medical resources in recen...

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