AIMC Topic: Aged

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Evaluating large language and large reasoning models as decision support tools in emergency internal medicine.

Computers in biology and medicine
BACKGROUND: Large Language Models (LLMs) hold promise for clinical decision support, but their real-world performance varies. We compared three leading models (OpenAI's "o1" Large Reasoning Model (LRM), Anthropic's Claude-3.5-Sonnet, and Meta's Llama...

Exploring the diagnostic potential of EEG theta power and interhemispheric correlation of temporal lobe activities in Alzheimer's Disease through random forest analysis.

Computers in biology and medicine
BACKGROUND: Considering the prevalence of Alzheimer's Disease (AD) among the aging population and the limited means of treatment, early detection emerges as a crucial focus area whereas electroencephalography (EEG) provides a promising diagnostic too...

Effect of Cumulative Exposure on the Efficacy of Paroxetine: A Population Pharmacokinetic-Pharmacodynamic and Machine Learning Analyses.

CPT: pharmacometrics & systems pharmacology
Selective serotonin reuptake inhibitors (SSRIs) are widely used in depression treatment. However, the relationship between treatment efficacy and plasma concentrations remains unclear. We assessed whether the anti-depressive response can be predicted...

The impact of machine learning on physical activity-related health outcomes: A systematic review and meta-analysis.

International nursing review
AIM: To analyze randomized controlled trials evaluating the effectiveness of machine learning (ML)-based interventions in promoting physical activity.

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

Computers in biology and medicine
BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that is known to have multifaceted impacts. However, as AKI is often detected too late, early prediction is crucial for timely intervention.

Resting-state functional MRI metrics to detect freezing of gait in Parkinson's disease: a machine learning approach.

Computers in biology and medicine
Among the symptoms that can occur in Parkinson's disease (PD), Freezing of Gait (FOG) is a disabling phenomenon affecting a large proportion of patients, and it remains not fully understood. Accurate classification of FOG in PD is crucial for tailori...

Fully automated image quality assessment based on deep learning for carotid computed tomography angiography: A multicenter study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To develop and evaluate the performance of fully automated model based on deep learning and multiple logistics regression algorithm for image quality assessment (IQA) of carotid computed tomography angiography (CTA) images.

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

Diabetes research and clinical practice
AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day and 90-day mortality in septic ICU patients.

MRI-based multimodal AI model enables prediction of recurrence risk and adjuvant therapy in breast cancer.

Pharmacological research
Timely intervention and improved prognosis for breast cancer patients rely on early metastasis risk detection and accurate treatment predictions. This study introduces an advanced multimodal MRI and AI-driven 3D deep learning model, termed the 3D-MMR...

Explainable machine learning for movement disorders - Classification of tremor and myoclonus.

Computers in biology and medicine
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.