Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images.

Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the SIIM-ISIC Melanoma Classification Challenge; however, these solutions leverage ensembles of complex deep neural architectures requiring immense storage and computation costs, and therefore may not be tractable. A recent movement for TinyML applications is integrating Double-Condensing Attention Condensers (DC-AC) into a self-attention neural network backbone architecture to allow for faster and more efficient computation.

A Direct Comparison of the Clinical Practice Patterns of Advanced Practice Providers and Doctors.

Background: Rising health care costs, physician shortages, and an aging patient population have increased the demand and utilization of advanced practice providers (APPs). Despite their expanding role in care delivery, little research has evaluated the care delivered by APPs compared with physicians.

Methods: We used clinical patient simulations to measure and compare the clinical care offered by APPs and physicians, collecting data from 4 distinct health care systems/hospitals in the United States between 2013 and 2017.

Engaging Primary Care Providers to Reduce Unwanted Clinical Variation and Support ACO Cost and Quality Goals: A Unique Provider-Payer Collaboration.

This project was undertaken to reduce unneeded variation among practicing primary care clinicians participating in an accountable care organization (ACO) and to raise quality and reduce costs. This real-world, quasi-controlled experiment compared ACO target improvements between 3 participating geographic regions and members within the ProHealth ACO against nonparticipating regions and members. The authors used a novel care standardization initiative to engage participating providers.

Dynamic CT for Parathyroid Adenoma Detection: How Does Radiation Dose Compare With Nuclear Medicine?

Objective: Dynamic CT is increasingly used for preoperative localization of parathyroid adenomas, but concerns remain about the radiation effective dose of CT compared with that of Tc-sestamibi scintigraphy. The purpose of this study was to compare the radiation dose delivered by three-phase dynamic CT with that delivered by Tc-sestamibi SPECT/CT performed in accordance with our current protocols and to assess the possible reduction in effective dose achieved by decreasing the scan length (i.e.