AIMC Topic: Aged, 80 and over
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Home-Based Cognitive Intervention for Healthy Older Adults Through Asking Robots Questions: Randomized Controlled Trial.
JMIR aging
Apr 22, 2024
BACKGROUND: Asking questions is common in conversations, and while asking questions, we need to listen carefully to what others say and consider the perspective our questions adopt. However, difficulties persist in verifying the effect of asking ques...
Social Workers' Perspectives on Socially Isolated Older Adults Living with a Robot Companion.
Journal of gerontological social work
Apr 21, 2024
Addressing depression and social isolation among solo-living older adults in South Korea requires a multi-faceted approach. This study aims to explore the advantages and obstacles of a robotic elder care program by analyzing social workers' viewpoint...
Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.
Abdominal radiology (New York)
Apr 20, 2024
PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.
Magnetic Resonance Imaging
Image Interpretation, Computer-Assisted
Image Enhancement
Angiography, Digital Subtraction
Subtraction Technique
Middle Aged
Deep Learning
Liver Neoplasms
Carcinoma, Hepatocellular
Contrast Media
Aged, 80 and over
Adult
Sensitivity and Specificity
Male
Humans
Algorithms
Retrospective Studies
Female
Aged
Validation of prostate and breast cancer detection artificial intelligence algorithms for accurate histopathological diagnosis and grading: a retrospective study with a Japanese cohort.
Pathology
Apr 19, 2024
Prostate and breast cancer incidence rates have been on the rise in Japan, emphasising the need for precise histopathological diagnosis to determine patient prognosis and guide treatment decisions. However, existing diagnostic methods face numerous c...
A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.
Journal of thrombosis and haemostasis : JTH
Apr 19, 2024
BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for ...
Machine learning for predicting colon cancer recurrence.
Surgical oncology
Apr 19, 2024
INTRODUCTION: Colorectal cancer (CRC) is a global public health concern, ranking among the most commonly diagnosed malignancies worldwide. Despite advancements in treatment modalities, the specter of CRC recurrence remains a significant challenge, de...
Predicting in-hospital mortality among patients admitted with a diagnosis of heart failure: a machine learning approach.
ESC heart failure
Apr 18, 2024
Existing risk prediction models for hospitalized heart failure patients are limited. We identified patients hospitalized with a diagnosis of heart failure between 7 May 2013 and 26 April 2022 from a large academic, quaternary care medical centre (tra...
Collagen and elastic fibers assessment of the human heart valves for age estimation in Thais using image analysis.
Forensic science, medicine, and pathology
Apr 18, 2024
The study investigated the relationship between the histological compositions of the tricuspid, pulmonary, mitral, and aortic valves, and age. All 85 fresh human hearts were obtained with an age range between 20 and 90 years. The central area of the ...
Union is strength: the combination of radiomics features and 3D-deep learning in a sole model increases diagnostic accuracy in demented patients: a whole brain 18FDG PET-CT analysis.
Nuclear medicine communications
Apr 18, 2024
OBJECTIVE: FDG PET imaging plays a crucial role in the evaluation of demented patients by assessing regional cerebral glucose metabolism. In recent years, both radiomics and deep learning techniques have emerged as powerful tools for extracting valua...
Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications.
British journal of anaesthesia
Apr 18, 2024
BACKGROUND: Timely detection of modifiable risk factors for postoperative pulmonary complications (PPCs) could inform ventilation strategies that attenuate lung injury. We sought to develop, validate, and internally test machine learning models that ...
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