A Qualitative Study of Primary Care Physicians' Approaches to Caring for Adult Adopted Patients.

Purpose: Adoption has lifelong health implications for 7.8 million adopted people and their families in the United States. The majority of adoptees have limited family medical history (LFMH).

Engaging Patients with Headache in the Veterans Health Administration (VHA): ACTIvated Veterans Engagement Group (ACTIVE) to Improve Delivery of Patient-Centered Headache Services.

In 2018, the Veterans Health Administration (VHA) established the original 19 Headache Centers of Excellence (HCoE) program, and an evaluation center. This study utilized a Veteran engagement group method to elicit input from Veteran patients living with chronic headache on daily needs, social determinants of health, and preferences and suggestions for headache programs, services, and research priorities. Four engagement groups were conducted between July 13 and August 22 of 2022 with Veterans who experience headache and received care at a VHA HCoE.

Deep Learning Models for Automatic Classification of Anatomic Location in Abdominopelvic Digital Subtraction Angiography.

Purpose: To explore the information in routine digital subtraction angiography (DSA) and evaluate deep learning algorithms for automated identification of anatomic location in DSA sequences.

Methods: DSA of the abdominal aorta, celiac, superior mesenteric, inferior mesenteric, and bilateral external iliac arteries was labeled with the anatomic location from retrospectively collected endovascular procedures performed between 2010 and 2020 at a tertiary care medical center. "Key" images within each sequence demonstrating the parent vessel and the first bifurcation were additionally labeled.

A retrospective cohort study examining the outcomes of patients who present for fertility care and exceed a set body mass index threshold for treatment.

Objective: To evaluate the characteristics of patients who exceeded the body mass index (BMI) threshold for fertility treatment at their initial visit and identify those for whom treatment would be constrained.

Design: Retrospective cohort study.

Setting: Academic medical center.

Envisioning a path from the Internet of Medical Things to improved fertility care access: a mini-review.

Devices that function within a network of interconnected systems and are equipped with sensors, software, and tools designed to collect and exchange data are widely known as the Internet of Things (IoT). In recent years, the rapid growth of IoT technology has sparked significant interest in leveraging these systems to enhance healthcare delivery across various medical fields, including fertility care and assisted reproductive technology. The subset of IoT devices applied within the healthcare sector is referred to as the Internet of Medical Things (IoMT).