Utilizing the 4Ms framework to create a structure and process to support voluntary health assessments in affordable housing.

Background: A growing number of older adults live in senior affordable housing, many with limited support systems and representing underserved or disadvantaged populations. Staff in these buildings are in a unique position to identify and address the healthcare and biopsychosocial needs of their residents and link them to services and supports.

Methods: Staff in four affordable housing sites received training on the 4Ms approach to caring for older adults and conducting resident health assessments.

Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head.

Background And Purpose: Mass effect and vasogenic edema are critical findings on CT of the head. This study compared the accuracy of an artificial intelligence model (Annalise Enterprise CTB) with consensus neuroradiologists' interpretations in detecting mass effect and vasogenic edema.

Materials And Methods: A retrospective stand-alone performance assessment was conducted on data sets of noncontrast CT head cases acquired between 2016 and 2022 for each finding.

Not without Context-A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts.

Rationale And Objectives: Brain tumor segmentations are integral to the clinical management of patients with glioblastoma, the deadliest primary brain tumor in adults. The manual delineation of tumors is time-consuming and highly provider-dependent. These two problems must be addressed by introducing automated, deep-learning-based segmentation tools.

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty.

The "Crossing Collection Sign": A Diagnostic Tool on Spine Magnetic Resonance Imaging For Localizing Cerebrospinal Fluid Leak.

Objective: The aim of the study is to determine whether the site of "cross" between ventral and dorsal spinal longitudinal extradural CSF collections (SLECs) seen on magnetic resonance imaging during initial workup of patients with suspected CSF leaks can predict the subsequently confirmed leakage site on computed tomography myelography or surgical repair.

Methods: This was an institutional review board-approved, retrospective study performed from 2006 to 2021. Patients with SLECs who underwent total spine magnetic resonance imaging at our institution, followed by myelography and/or surgical repair for CSF leak, were included.