AIMC Topic: Middle Aged

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"Identifying complication risk factors in reduction mammaplasty: a single-center analysis of 1021 patients applying machine learning methods".

Updates in surgery
Various surgical approaches and pedicles have been described to ensure safe and satisfactory results in reduction mammaplasty. Although different breasts require different techniques, complications are common. This study aims to assess the incidence ...

Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.

Photodiagnosis and photodynamic therapy
OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with an artificial intelligence (AI) reading platform for large-scale screening of diabetic retinopathy (DR).

Metabolic phenotyping combined with transcriptomics metadata fortifies the diagnosis of early-stage Hepatocellular carcinoma.

Journal of advanced research
INTRODUCTION: The low sensitivity of alpha-fetoprotein (AFP) renders it unsuitable as a stand-alone marker for early hepatocellular carcinoma (eHCC) surveillance. Therefore, additional blood-based biomarkers with enhanced sensitivities are required.

Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study.

Cancer research and treatment
PURPOSE: We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous int...

The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVE: The incidence of non-melanoma skin cancers, encompassing basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), is on the rise globally and new methods to improve skin malignancy diagnosis are necessary. This study aims t...

Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor.

Cancer
BACKGROUND: Nonadherence to imatinib is common in patients with gastrointestinal stromal tumor (GIST), which is associated with poor prognosis and financial burden. The primary aim of this study was to investigate the adherence rate in patients with ...

Deep Learning Based Shear Wave Detection and Segmentation Tool for Use in Point-of-Care for Chronic Liver Disease Assessments.

Ultrasound in medicine & biology
OBJECTIVE: As metabolic dysfunction-associated steatotic liver disease (MASLD) becomes more prevalent worldwide, it is imperative to create more accurate technologies that make it easy to assess the liver in a point-of-care setting. The aim of this s...

MyofAPPcial: Construct validity of a novel technological aid for improving clinical reasoning in the management of myofascial pain syndrome.

European journal of clinical investigation
BACKGROUND: Physiotherapists encounter challenges in diagnosing myofascial trigger points (MTrPs), which are crucial for managing myofascial pain but difficult due to their complex referred pain patterns. We aimed to assess if an interactive software...

A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.

Journal of clinical epidemiology
OBJECTIVE: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteristics, along with limited physician awareness of the disease's early symptoms. Early and accurate di...