Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis.

Coronary artery disease is a leading cause of death worldwide. There has been a myriad of advancements in the field of cardiovascular imaging to aid in diagnosis, treatment, and prevention of coronary artery disease. The application of artificial intelligence in medicine, particularly in cardiovascular medicine has erupted in the past decade. This article serves to highlight the highest yield articles within cardiovascular imaging with an emphasis on coronary CT angiography methods for % stenosis evaluation and atherosclerosis quantification for the general cardiologist. The paper finally discusses the evolving paradigm of implementation of artificial intelligence in real world practice.

Thyrotoxicosis: a rare presentation of molar pregnancy.

A 49-year-old woman, G8P7, presented with 1 week of worsening vaginal bleeding and abdominal cramps in the setting of a recently discovered unplanned pregnancy. Vaginal ultrasound findings and a significantly elevated human chorionic gonadotropin (hCG) level were concerning for molar pregnancy. She developed signs of hyperthyroidism on the night of admission, for which the endocrinology team was consulted. Laboratory data were consistent with hyperthyroidism. The patient was believed to have thyrotoxicosis secondary to molar pregnancy with concern for impending thyroid storm. Her mental health disorder and bacteraemia made taking care of her further challenging. She was started on a beta-blocker, antithyroid agent and intravenous corticosteroids. She underwent an uncomplicated suction dilation and curettage (D&C), with resolution of her symptoms a few days after. At a follow-up appointment, the patient continued to be asymptomatic and was feeling well.

What patients see online: assessing the online identities of Pennsylvania dermatologists.

INTRODUCTION: Patients use the internet to search for health-related information. We sought to characterize the information that patients find when searching for dermatologists on Google. METHODS: The Centers for Medicare and Medicaid Services (CMS) Physician Comparable Downloadable File was utilized to identify all Medicare-participating dermatologists practicing in Pennsylvania (PA). A custom Google-based search engine was used to search each dermatologist. Up to the top 10 results for each physician were then sorted into: (1) physician, hospital, or healthcare system, (2) third-party, (3) social media, (4) academic journal articles, or (5) other. RESULTS: Within the CMS, 519 health care providers (53.9% male, 46.1% female) self-identified as dermatologists practicing in PA. At least one search result was obtained for each physician (4,963 total search results). About 30.6% (1,519) search results were hospital, health system, or physician-controlled websites, and 26.6% (1,318) were third-party websites (1,318; 26.6%). Social media websites accounted for 601 (12.1%) hits whereas peer-reviewed academic journal websites generated 135 (2.7%) results. One-way chi-square analysis showed domains were not randomly distributed across the five categories (P<0.0001). CONCLUSION: Dermatologists should be better aware of their digital presence and the strategies to better control their online identity.

Reputation Management and Content Control: An Analysis of Radiation Oncologists' Digital Identities.

INTRODUCTION: Google is the most popular search engine in the United States, and patients are increasingly relying on online webpages to seek information about individual physicians. This study aims to characterize what patients find when they search for radiation oncologists online. METHODS AND MATERIALS: The Centers for Medicare and Medicaid Services (CMS) Physician Comparable Downloadable File was used to identify all Medicare-participating radiation oncologists in the United States and Puerto Rico. Each radiation oncologist was characterized by medical school education, year of graduation, city of practice, gender, and affiliation with an academic institution. Using a custom Google-based search engine, up to the top 10 search results for each physician were extracted and categorized as relating to: (1) physician, hospital, or health care system; (2) third-party; (3) social media; (4) academic journal articles; or (5) other. RESULTS: Among all health care providers in the United States within CMS, 4443 self-identified as being radiation oncologists and yielded 40,764 search results. Of those, 1161 (26.1%) and 3282 (73.9%) were classified as academic and nonacademic radiation oncologists, respectively. At least 1 search result was obtained for 4398 physicians (99.0%). Physician, hospital, and health care-controlled websites (16,006; 39.3%) and third-party websites (10,494; 25.7%) were the 2 most often observed domain types. Social media platforms accounted for 2729 (6.7%) hits, and peer-reviewed academic journal websites accounted for 1397 (3.4%) results. About 6.8% and 6.7% of the top 10 links were social media websites for academic and nonacademic radiation oncologists, respectively. CONCLUSIONS: Most radiation oncologists lack self-controlled online content when patients search within the first page of Google search results. With the strong presence of third-party websites and lack of social media, opportunities exist for radiation oncologists to increase their online presence to improve patient-provider communication and better the image of the overall field. We discuss strategies to improve online visibility.