AIMC Topic: Adult

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Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images.

Physical and engineering sciences in medicine
Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long time. In fact, individuals with SZ experience a blurred line between fantasy and reality, leading to a lack of awareness about their condition, which can pose s...

Ultrasound-Based Deep Learning Radiomics Nomogram for the Assessment of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: The aim of this study was to develop a deep learning radiomics nomogram (DLRN) based on B-mode ultrasound (BMUS) and color doppler flow imaging (CDFI) images for preoperative assessment of lymphovascular invasion (LVI) statu...

Age and medial compartmental OA were important predictors of the lateral compartmental OA in the discoid lateral meniscus: Analysis using machine learning approach.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The objective of this study was to develop a machine learning model that would predict lateral compartment osteoarthritis (OA) in the discoid lateral meniscus (DLM), from which to then identify factors contributing to lateral compartment OA,...

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

World journal of surgery
INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) can be an effective treatment for these patients. However, the p...

The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome.

Cell host & microbe
The mechanisms underlying the many phenotypic manifestations of post-acute COVID-19 syndrome (PACS) are poorly understood. Herein, we characterized the gut microbiome in heterogeneous cohorts of subjects with PACS and developed a multi-label machine ...

Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS.

Abdominal radiology (New York)
PURPOSE: To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical ...

Tool or Tyrant: Guiding and Guarding Generative Artificial Intelligence Use in Nursing Education.

Creative nursing
As artificial intelligence (AI) continues to evolve rapidly, its integration into nursing education is inevitable. This article presents a narrative exploring the implementation of generative AI in nursing education and offers a guide for its strateg...

Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018-2020 FEMA National Household Survey.

International journal of environmental research and public health
Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This st...

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on ultrasound: a retrospective study.

BMC cancer
BACKGROUND: To develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis.