AIMC Topic: Middle Aged

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Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.

Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determining bone mineral density (BMD) in chronic obstructive pulmonary disease (COPD) patients using chest computed tomography (CT) scans.

Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.

PloS one
PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep learning models in accurately diagnosing fatty liver.

Deep learning based screening model for hip diseases on plain radiographs.

PloS one
INTRODUCTION: The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs.

Optimising test intervals for individuals with type 2 diabetes: A machine learning approach.

PloS one
BACKGROUND: Chronic disease monitoring programs often adopt a one-size-fits-all approach that does not consider variation in need, potentially leading to excessive or insufficient support for patients at different risk levels. Machine learning (ML) d...

Objectifying aesthetic outcomes following face transplantation - the AI research metrics model (CAARISMA® ARMM).

Journal of stomatology, oral and maxillofacial surgery
BACKGROUND: Face transplantation (FT) offers a reconstructive option for patients with severe facial disfigurements by restoring both function and appearance. Aesthetic outcomes, which are crucial to psychological well-being and social reintegration,...

Using ChatGPT-4 in visual field test assessment.

Clinical & experimental optometry
CLINICAL RELEVANCE: Visual field testing is essential in the diagnosis and management of various ophthalmic diseases, particularly glaucoma. Integrating ChatGPT-4 into the interpretation of these tests has the potential to aid clinical decision makin...

Association of visceral fat obesity with structural change in abdominal organs: fully automated three-dimensional volumetric computed tomography measurement using deep learning.

Abdominal radiology (New York)
The purpose of this study was to explore the association between structural changes in abdominal organs and visceral fat obesity (VFO) using a fully automated three-dimensional (3D) volumetric computed tomography (CT) measurement method based on deep...

Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.

Annals of the rheumatic diseases
OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular contributors. Biofluids contain microRNAs and metabolites that can be measured by omic technologies. Multimodal deep learning is adept at uncovering ...

Image quality and diagnostic performance of deep learning reconstruction for diffusion- weighted imaging in 3 T breast MRI.

European journal of radiology
PURPOSE: This study aimed to assess the image quality and the diagnostic value of deep learning reconstruction (DLR) for diffusion-weighted imaging (DWI) compared with conventional single-shot echo-planar imaging (ss-EPI) in 3 T breast MRI.