AIMC Topic: Aged

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Artificial Intelligence Model for Time Series Classification: Prediction of Delayed Balloon Expulsion Test Using High-Resolution Anorectal Manometry Data and Time-Series Integrated Pressurized Volume.

Neurogastroenterology and motility
BACKGROUND: We previously demonstrated the novel concept of using the integrated pressurized volume (IPV) with high-resolution anorectal manometry (HRAM) and found that it was predictive of delayed balloon expulsion (BE) test results. However, previo...

Estimating depression severity in narrative clinical notes using large language models.

Journal of affective disorders
BACKGROUND: Depression treatment guidelines emphasize measurement-based care using patient-reported outcome measures, yet their impact on narrative documentation quality remains underexplored.

5-5-5 ABRT (Dose of 5 Gy per Fraction for up to 5 Fractions Over 5 Weeks Adaptive Bridging Radiation Therapy)-Artificial Intelligence Enters the CAR (-T) (Chimeric Antigen Receptor-T) in Relapsed/Refractory Large B Cell Lymphoma.

International journal of radiation oncology, biology, physics
PURPOSE: Bridging radiation therapy (BRT) is effective for local control in patients with relapsed or refractory large B cell lymphoma who are undergoing chimeric antigen receptor (CAR) T cell therapy. We hypothesized that adaptive BRT (ABRT), which ...

Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

Academic radiology
RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, yet its neural mechanisms are poorly understood. This study investigates structural and functional brain network reconfiguration in ESRD patients transi...

A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.

The Journal of pathology
Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichment of distinct T-cell subpopulations has been determined to impact the response to immune checkpoint ...

Effect of a ChatGPT-based digital counseling intervention on anxiety and depression in patients with cancer: A prospective, randomized trial.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Psychological distress is prevalent among newly diagnosed cancer patients, often exacerbating treatment-related anxiety and depression. Artificial intelligence (AI)-driven interventions, such as large language models (LLMs), offer scalabl...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

Orthopaedic surgery
OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Studies have shown that in emergency settings, the misdiagnosis rate of hand/wrist fractures can reach ...

Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.

Breast cancer research : BCR
BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a MRI-based enhanced self-attention network (MESN) for ...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Scientific reports
Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD), and it increases the risk of osteoporosis and fractures. This study aimed to develop predictive m...

Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient.

Scientific reports
Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on EEG for assessing brain injury, with some exploring...