State Required CME

Profiling and Predicting Faculty Assessment Behavior in Surgical Education

To study and profile the digital assessment behaviors of surgical faculty and residents, and to build a classifier to predict assessment completion, enhancing formative feedback initiatives. As competency-based paradigms are integrated into surgical training, developing digital education tools for measuring competency and providing rapid feedback is crucial. Simply making assessments available is ...

Towards Inpatient Discharge Summary Automation via Large Language Models: A Multidimensional Evaluation with a HIPAA-Compliant Instance of GPT-4o and Clinical Expert Assessment

Large language models (LLMs) have demonstrated potential to automate clinical documentation tasks that may reduce clinician burden, such as generation of hospital discharge summaries. Prior research used older LLMs and limited data, raising concerns about fabrications and omissions. In this study, we evaluated the automatic generation of inpatient Internal Medicine discharge summaries using a HIPA...

Changes in psychiatric documentation and treatment in primary care with artificial intelligence scribe use

Despite increasingly widespread use of artificial intelligence-driven ambient scribes in medicine, the extent to which they may impact clinician pract...

DermAssist: A Hybrid Vision Transformer System for Skin Lesion Diagnosis with Automated Alerting and Dual-Sided Portals

Skin cancer, one of the most prevalent forms of cancer globally, demands early and accurate diagnosis to improve patient outcomes. In this paper, we p...

Large Language Models Improve Coding Accuracy and Reimbursement in a Neonatal Intensive Care Unit

Diagnosis coding is essential for clinical care, research validity, and hospital reimbursement. In neonatal settings, manual coding is frequently erro...

Evaluating Generative AI as an Educational Tool for Radiology Resident Report Drafting

Radiology residents require timely, personalized feedback to develop accurate image analysis and reporting skills. Increasing clinical workload often ...

Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation

To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...

Are Explanations Helpful? A Comparative Analysis of Explainability Methods in Skin Lesion Classifiers

Deep Learning has shown outstanding results in computer vision tasks; healthcare is no exception. However, there is no straightforward way to expose...

HOPPR Medical-Grade Platform for Medical Imaging AI

Technological advances in artificial intelligence (AI) have enabled the development of large vision language models (LVLMs) that are trained on mill...

Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection

As AI systems increasingly integrate into critical societal sectors, the demand for robust privacy-preserving methods has escalated. This paper intr...

GENEVIC: GENetic data Exploration and Visualization via Intelligent interactive Console.

SUMMARY: The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-dr...

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.

OBJECTIVES: To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiolo...

Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory

Privacy research has attracted wide attention as individuals worry that their private data can be easily leaked during interactions with smart devic...

AI Chatbots, Health Privacy, and Challenges to HIPAA Compliance.

Artificial Intelligence Competencies in Postgraduate Medical Training in Germany.

Routine medical care is to be transformed by the introduction of artificial intelligence (AI), requiring medical professionals to acquire a novel set ...

AI technology for remote clinical assessment and monitoring.

OBJECTIVE: To report the clinical validation of an innovative, artificial intelligence (AI)-powered, portable and non-invasive medical device called W...

A Preliminary Study of Predicting Effectiveness of Anti-VEGF Injection Using OCT Images Based on Deep Learning.

Deep learning based radiomics have made great progress such as CNN based diagnosis and U-Net based segmentation. However, the prediction of drug effec...

In vitro cytotoxic, antioxidant, antibacterial and antifungal activity of Saussurea heteromalla indigenous to Pakistan.

Medicinal plants are proven to reveal vast promising potential providing novel drug candidates to combat health-related problems. The aim of current s...

Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning.

Assess the efficacy of deep convolutional neural networks (DCNNs) in detection of critical enteric feeding tube malpositions on radiographs. 5475 de-i...

De-identification of patient notes with recurrent neural networks.

OBJECTIVE: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority o...