Taba Binary, Multinomial, and Ordinal Regression Models: New Machine Learning Methods for Classification.

The classification methods of machine learning have been widely used in almost every discipline. A new classification method, called Taba regression, was introduced for analyzing binary, multinomial, and ordinal outcomes. To evaluate the performance of Taba regression, liver cirrhosis data obtained from a Mayo Clinic study were analyzed.

Pilot study of topical ruxolitinib demonstrates efficacy and blunting of heterogeneous inflammatory processes in mild hidradenitis suppurativa.

Background: Therapeutic options for mild hidradenitis suppurativa (HS) represent a significant gap in the current treatment landscape, with no FDA approved therapies for early stage HS. Topical JAnus Kinase inhibitors (JAKi) are a compelling option due to the known upregulation of inflammatory JAK signaling in HS lesions and the recent success of systemic JAKi for moderate to severe HS.

Objectives: This is a pilot, single-site, open-label, prospective 24-week clinical trial with topical ruxolitinib (NCT04414514).

The Relationship of Pork Meat Consumption with Nutrient Intakes, Diet Quality, and Biomarkers of Health Status in Korean Older Adults.

Background: Pork meat is a widely consumed protein food with the potential to differentially affect health and nutritional status across social and cultural contexts.

Objectives: We evaluated the association between pork meat consumption and nutrient intake, diet quality, and biomarkers of health among older adults (age ≥ 65 years) in Korea.

Methods: Our analyses utilized dietary and health examination data from the 2016-2020 Korean National Health and Nutrition Examination Survey ( = 2068).

Accelerated phase-contrast magnetic resonance imaging with use of resolution enhancement generative adversarial neural network.

Background: Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging.

Methods: CRISPFlow was built on the super-resolution generative adversarial network.

Late gadolinium enhancement cardiovascular magnetic resonance with generative artificial intelligence.

Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging enables imaging of scar/fibrosis and is a cornerstone of most CMR imaging protocols. CMR imaging can benefit from image acceleration; however, image acceleration in LGE remains challenging due to its limited signal-to-noise ratio. In this study, we sought to evaluate a rapid two-dimensional (2D) LGE imaging protocol using a generative artificial intelligence (AI) algorithm with inline reconstruction.