AIMC Topic: Middle Aged

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[Ga]Ga-PSMA-11 PET Tumor Volume Predicts Overall Survival of Patients with Metastatic Prostate Cancer Undergoing Taxane-Based Chemotherapy.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Prostate-specific membrane antigen (PSMA) PET has the potential to monitor the response to taxane-based chemotherapy in patients with prostate cancer and shows promise for predicting outcomes and improving response evaluation. This retrospective stud...

Machine learning models for predicting renal injury in patients with gout.

Renal failure
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.

From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy.

World journal of urology
OBJECTIVE: Percutaneous nephrolithotomy is the gold standard for treating large kidney stones. However, traditional scoring systems and logistic regression-based models have limited predictive power due to their reliance on linear assumptions. This s...

Exploring multidrug resistance patterns in community-acquired urinary tract infections with machine learning.

Antimicrobial agents and chemotherapy
While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remain underexplored. This study used association-set mining to explore resistance associations within i...

Local large arterial perivascular adipose tissue metabolic and anatomical features are associated with hypertensive clinical outcomes: a PET/CT-based study.

Annals of medicine
OBJECTIVE: This study investigated the relationship between anatomical and metabolic characteristics of large arterial perivascular adipose tissue (PVAT) and hypertensive clinical outcomes using positron emission tomography-computed tomography (PET/C...

Primary tumor resection: a new hope or an old illusion for patients with metastatic non-small cell lung neuroendocrine tumors?

World journal of surgical oncology
OBJECTIVES: This study aimed to investigate the impact of primary tumor resection (PTR) on survival outcomes for patients with metastatic non-small cell neuroendocrine tumors (mNSCLC-NETs), develop a predictive model to identify which patients may be...

A machine learning model including pentraxin-3 as predictor of outcomes in community-acquired pneumonia.

Journal of translational medicine
BACKGROUND: The clinical diagnosis, severity assessment, and outcome prognostication of community-acquired pneumonia (CAP) remain challenging due to the complex disease pathophysiology. Accurate outcome prediction is crucial for optimizing patient ma...

An MRI-based radiomics framework for early identification and progression stratification in knee osteoarthritis: data from the osteoarthritis initiative.

BMC musculoskeletal disorders
OBJECTIVES: To develop a cascaded machine learning model based on MRI radiomics features from cartilage and subchondral bone to predict the incidence and progression of knee osteoarthritis (KOA), thereby addressing the need for early intervention in ...

Characteristics of brain glucose metabolism in Parkinson's disease patients with freezing of gait: a study based on F-FDG PET imaging and deep learning.

BMC neurology
OBJECTIVE: Freezing of gait (FOG) is a common gait disorder in the advanced stages of Parkinson's disease (PD), closely associated with impaired balance and executive function. This study aimed to investigate specific changes in brain glucose metabol...

Application of interpretable machine learning to predict activities of daily living disability in sarcopenia: insights from the CHARLS dataset.

BMC geriatrics
PURPOSE: The decline in activities of daily living (ADL) among older persons is a significant public health concern. Sarcopenia is a major risk factor for ADL disability. This study aimed to develop and validate an interpretable machine learning (IML...