AIMC Topic: Middle Aged

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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT.

Stroke and vascular neurology
BACKGROUND: CT is commonly used to image patients with ischaemic stroke but radiologist interpretation may be delayed. Machine learning techniques can provide rapid automated CT assessment but are usually developed from annotated images which necessa...

Comparative analysis of outcomes in high KDPI spectrum kidney transplants using unsupervised machine learning algorithm.

PloS one
BACKGROUND: The Kidney Donor Profile Index (KDPI) is a continuous metric used to estimate the risk of allograft failure for kidneys from deceased donors. Lower KDPI scores are associated with longer post-transplant kidney function. This study aims to...

Hospital acquired drug resistant pathogens infections in patients with viral respiratory tract infections: a retrospective study.

BMC infectious diseases
BACKGROUND: Viral respiratory infections (VRTIs) caused by influenza (Flu) and COVID-19 pose significant global health challenges. Clinical outcomes are further exacerbated by infections with hospital acquired drug resistant pathogens (DRPs).

Prediction of Mini-Mental State Examination Scores for Cognitive Impairment and Machine Learning Analysis of Oral Health and Demographic Data Among Individuals Older Than 60 Years: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: As the older population grows, so does the prevalence of cognitive impairment, emphasizing the importance of early diagnosis. The Mini-Mental State Examination (MMSE) is vital in identifying cognitive impairment. It is known that degraded...

Development of an alcohol biosensor non-wear algorithm: laboratory-based machine learning and field-based deployment.

Scientific reports
Wrist-worn alcohol biosensors can continuously track alcohol consumption, but their measurements are disrupted when the device is removed. Left unaddressed, non-wear data compromises observations of alcohol use and subsequent predictions of intoxicat...

Survival impact of adjuvant radiotherapy in early stage low risk elderly male breast cancer patients treated with breast conserving surgery.

Scientific reports
Our study aimed to evaluate the survival impact of adjuvant radiotherapy (RT) following breast-conserving surgery (BCS) in elderly male patients with early-stage, low-risk breast cancer (node-negative, HR+), and to identify RT-benefiting subgroups us...

Machine learning to predict bacteriuria in the emergency department.

Scientific reports
Urinary tract infections (UTIs) are among the most common bacterial infections, yet they are both frequently misdiagnosed and inappropriately treated. We aimed to determine whether a machine learning model could accurately predict bacteriuria by usin...

Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data.

Scientific reports
Glioblastoma is an aggressive, malignant primary brain tumour and the most prevalent histological type of glioma. Our study attempted to investigate the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in Asian patie...

A novel MRI-based habitat analysis and deep learning for predicting perineural invasion in prostate cancer: a two-center study.

BMC cancer
BACKGROUND: To explore the efficacy of a deep learning (DL) model in predicting perineural invasion (PNI) in prostate cancer (PCa) by conducting multiparametric MRI (mpMRI)-based tumor heterogeneity analysis.