AIMC Topic: Aged, 80 and over

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Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.

PloS one
Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. ...

How people with dementia perceive a therapeutic robot called PARO in relation to their pain and mood: A qualitative study.

Journal of clinical nursing
BACKGROUND: Interacting with social robots, such as the robotic seal PARO, has been shown to improve mood and acute pain for people with dementia. Little attention has been paid to the effect of PARO on people with dementia and chronic pain.

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

JAMA network open
IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and r...

Effectiveness of Intervention Based on End-effector Gait Trainer in Older Patients With Stroke: A Systematic Review.

Journal of the American Medical Directors Association
OBJECTIVE: The objective of the article is to analyze the effects of the end-effector technology for gait rehabilitation on acute, subacute, and chronic stroke in order to verify the efficacy of the treatment in older people, based on evidence from r...

Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept.

Clinical radiology
AIM: To investigate the feasibility of applying a deep convolutional neural network (CNN) for detection/localisation of acute proximal femoral fractures (APFFs) on hip radiographs.

Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics.

IEEE journal of biomedical and health informatics
OBJECTIVE: Histologic grade and Ki-67 proliferation status are important clinical indictors for breast cancer prognosis and treatment. The purpose of this study is to improve prediction accuracy of these clinical indicators based on tumor radiomic an...

Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists.

Scientific reports
Computer-aided diagnosis (CAD) systems hold potential to improve the diagnostic accuracy of thyroid ultrasound (US). We aimed to develop a deep learning-based US CAD system (dCAD) for the diagnosis of thyroid nodules and compare its performance with ...

Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.

Scientific reports
Radiogenomics investigates the relationship between imaging phenotypes and genetic expression. Breast cancer is a heterogeneous disease that manifests complex genetic changes and various prognosis and treatment response. We investigate the value of m...

Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

Journal of cutaneous pathology
PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which ...

Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions.

Ultrasound in medicine & biology
The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for cla...