AIMC Topic: Aged

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Improving Clinically Significant Prostate Cancer Detection with a Multimodal Machine Learning Approach: A Large-Scale Multicenter Study.

Radiology. Imaging cancer
Purpose To develop and prospectively validate a clinical and radiologic model to predict clinically significant prostate cancer (csPCa) using biparametric MRI (bpMRI). Materials and Methods Retrospective data (acquired before March 31, 2022) from 12 ...

Deep Learning-Enhanced CTA for Noninvasive Prediction of First Variceal Haemorrhage in Cirrhosis: A Multi-Centre Study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: The first variceal haemorrhage (FVH) is a life-threatening complication of liver cirrhosis that requires timely intervention; however, noninvasive tools for accurately predicting FVH remain limited. This study aimed to develop no...

Machine Learning-Based Flap Takeback Prediction Modeling: Theory for a Real-Time, Patient-Specific Postoperative Flap Monitoring and Alert System.

Microsurgery
BACKGROUND: Postoperative free flap monitoring is crucial yet taxing, requiring frequent and often subjective assessments to detect early signs of compromise. The present study aims to develop a machine learning model to predict the risk of flap take...

GPSai: A Clinically Validated AI Tool for Tissue of Origin Prediction during Routine Tumor Profiling.

Cancer research communications
UNLABELLED: A subset of cancers present with unclear or potentially incorrect primary histopathologic diagnoses, including cancers of unknown primary (CUP). We aimed to develop and validate an artificial intelligence (AI) tool, Genomic Probability Sc...

A Conversational Robot for Cognitively Impaired Older People Who Live Alone: An Exploratory Feasibility Study.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Social isolation and loneliness are significant risk factors for poor mental health in older adults, particularly those living alone with cognitive impairment. Socially assistive robots (SARs) offer a promising approach to enhance social ...

Simultaneous T and ADC Mapping of Acute-to-Chronic Ischemic Stroke With Multiple Overlapping-Echo Detachment Imaging.

NMR in biomedicine
Multiparametric quantitative MRI based on multiple overlapping-echo detachment imaging (MQMOLED) can simultaneously quantify T and ADC with whole brain coverage within 40 s. T and ADC play an important role in the assessment and management of ischemi...

A preliminary exploration of surgical strategies for solitary papillary thyroid carcinoma on the isthmus.

Oral oncology
BACKGROUND: For solitary papillary thyroid carcinoma on the isthmic (SPTCI), there are currently no specific guidelines for the extent of resection and lymph node dissection. This study aims to explore the surgical strategies suitable for patients wi...

`Probabilistic ensemble learning for prediction of stroke thrombectomy outcomes from the NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) Acute Ischemic Stroke Registry.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke (AIS). The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-ope...

Single Inspiratory Chest CT-based Generative Deep Learning Models to Evaluate Functional Small Airways Disease.

Radiology. Artificial intelligence
Purpose To develop a deep learning model that uses a single inspiratory chest CT scan to perform parametric response mapping (PRM) and predict functional small airways disease (fSAD). Materials and Methods In this retrospective study, predictive and ...

A Deep Learning Model for Comprehensive Automated Bone Lesion Detection and Classification on Staging Computed Tomography Scans.

Academic radiology
RATIONALE AND OBJECTIVES: A common site of metastases for a variety of cancers is the bone, which is challenging and time consuming to review and important for cancer staging. Here, we developed a deep learning approach for detection and classificati...