[Selection of the biopsy procedure-critical for dermatopathological diagnostics].

Skin biopsy is one of the most frequently performed diagnostic measures in dermatological practice. Depending on the diagnostic question, the selection of the type of biopsy procedure and the biopsy location can have a considerable influence on histological assessment. Depending on the disease, different aspects must be taken into account for a precise diagnosis.

Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.

Diagnostic errors in health care pose significant risks to patient safety and are disturbingly common. In the emergency department (ED), the chaotic and high-pressure environment increases the likelihood of these errors, as emergency clinicians must make rapid decisions with limited information, often under cognitive overload. Artificial intelligence (AI) offers promising solutions to improve diagnostic errors in three key areas: information gathering, clinical decision support (CDS), and feedback through quality improvement.

Learning from the EHR to implement AI in healthcare.

The introduction of the electronic health record was heralded as a technology solution to improve care quality and efficiency, but these tools have contributed to increased administrative burden and burnout for clinicians. Today, artificial intelligence is receiving much of the same attention and promises as electronic health records. Can healthcare learn from the failures of electronic health records to maximize the potential of artificial intelligence?

Thick Data Analytics (TDA): An Iterative and Inductive Framework for Algorithmic Improvement.

A gap remains between developing risk prediction models and deploying models to support real-world decision making, especially in high-stakes situations. Human-experts' reasoning abilities remain critical in identifying potential improvements and ensuring safety. We propose a (TDA) framework for eliciting and combining expert-human insight into the evaluation of models.

Dermatomyositis-like skin eruptions under hydroxyurea therapy conceal TP53-mutated atypical keratinocytes: A histopathologic and molecular pathologic case series.

Hydroxyurea is an antimetabolite that inhibits DNA synthesis and is used as a treatment option in chronic myeloproliferative disorders. Rarely, "dermatomyositis (DM)-like" skin lesions are observed after long-term therapy. In this case series, five skin biopsies of four patients were evaluated by histology, immunohistochemistry, and next-generation sequencing of the TP53 gene locus.

The Role of Large Language Models in Transforming Emergency Medicine: Scoping Review.

Background: Artificial intelligence (AI), more specifically large language models (LLMs), holds significant potential in revolutionizing emergency care delivery by optimizing clinical workflows and enhancing the quality of decision-making. Although enthusiasm for integrating LLMs into emergency medicine (EM) is growing, the existing literature is characterized by a disparate collection of individual studies, conceptual analyses, and preliminary implementations. Given these complexities and gaps in understanding, a cohesive framework is needed to comprehend the existing body of knowledge on the application of LLMs in EM.

Real-Time Electronic Patient Portal Use Among Emergency Department Patients.

Importance: Patients with inequitable access to patient portals frequently present to emergency departments (EDs) for care. Little is known about portal use patterns among ED patients.

Objectives: To describe real-time patient portal usage trends among ED patients and compare demographic and clinical characteristics between portal users and nonusers.

A Conference (Missingness in Action) to Address Missingness in Data and AI in Health Care: Qualitative Thematic Analysis.

Background: Missingness in health care data poses significant challenges in the development and implementation of artificial intelligence (AI) and machine learning solutions. Identifying and addressing these challenges is critical to ensuring the continued growth and accuracy of these models as well as their equitable and effective use in health care settings.

Objective: This study aims to explore the challenges, opportunities, and potential solutions related to missingness in health care data for AI applications through the conduct of a digital conference and thematic analysis of conference proceedings.

Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review.

Background: Generative artificial intelligence (AI) technologies are increasingly being utilized across various fields, with considerable interest and concern regarding their potential application in medical education. These technologies, such as Chat GPT and Bard, can generate new content and have a wide range of possible applications.

Objective: This study aimed to synthesize the potential opportunities and limitations of generative AI in medical education.

Recurrence of a Cellular Blue Nevus with Satellitosis-A Diagnostic Pitfall with Clinical Consequences.

Blue nevus is a benign melanocytic lesion, typically asymptomatic and of unknown etiology. Several histologic and clinical variants have been distinguished, the most frequent being common blue nevus, cellular blue nevus, and combined blue nevus. Although melanocytic nevi with a satellite lesion are usually suggestive of locally advanced malignant melanoma, very few cases of blue nevi with satellite lesions have been reported.

Team is brain: leveraging EHR audit log data for new insights into acute care processes.

Objective: To determine whether novel measures of contextual factors from multi-site electronic health record (EHR) audit log data can explain variation in clinical process outcomes.

Materials And Methods: We selected one widely-used process outcome: emergency department (ED)-based team time to deliver tissue plasminogen activator (tPA) to patients with acute ischemic stroke (AIS). We evaluated Epic audit log data (that tracks EHR user-interactions) for 3052 AIS patients aged 18+ who received tPA after presenting to an ED at three Northern California health systems (Stanford Health Care, UCSF Health, and Kaiser Permanente Northern California).

Deep Learning Assisted Diagnosis of Onychomycosis on Whole-Slide Images.

Background: Onychomycosis numbers among the most common fungal infections in humans affecting finger- or toenails. Histology remains a frequently applied screening technique to diagnose onychomycosis. Screening slides for fungal elements can be time-consuming for pathologists, and sensitivity in cases with low amounts of fungi remains a concern.

Addressing Medicine's Dark Matter.

In the 20th century, the models used to predict the motion of heavenly bodies did not match observation. Investigating this incongruity led to the discovery of dark matter-the most abundant substance in the universe. In medicine, despite years of using a data-hungry approach, our models have been limited in their ability to predict population health outcomes-that is, our observations also do not meet our expectations.

Histopathological risk factors for malignancy in dermatomyositis.

Aims: To identify possible histopathological risk factors for malignancy in skin biopsies of dermatomyositis patients.

Methods And Results: We analysed clinical metadata and studied 30 skin biopsies of 11 patients with and 12 patients without associated malignancy, who were treated in one secondary and one tertiary German medical centre between 2009 and 2022 and fulfilling the EULAR/ACR classification criteria for dermatomyositis. Specimens were categorized by malignancy status and evaluated based on haematoxylin and eosin (H&E), periodic acid Schiff (PAS), Alcian Blue, and anti-CD123 immunohistochemistry stains.

Mobile application adjunct to the WHO basic emergency care course: a mixed methods study.

Objectives: The WHO developed a 5-day basic emergency care (BEC) course using the traditional lecture format. However, adult learning theory suggests that lecture-based courses alone may not promote long-term knowledge retention. We assessed whether a mobile application adjunct (BEC app) can have positive impact on knowledge acquisition and retention compared with the BEC course alone and evaluated perceptions, acceptability and barriers to adoption of such a tool.