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Evaluation of the Impact of the Sustainable Development Goals on an Activity Recognition Platform for Healthcare Systems.

Sensors (Basel, Switzerland)
The Sustainable Development Goals (SDGs), also known as the Global Goals, were adopted by the United Nations in 2015 as a universal call to end poverty, protect the planet and ensure peace and prosperity for all by 2030. The 17 SDGs have been designe...

The use of artificial intelligence to detect students' sentiments and emotions in gross anatomy reflections.

Anatomical sciences education
Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language process...

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

European radiology
OBJECTIVES: To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features and clinical characteristics for evaluating therapeutic response after neoadjuvant chemotherapy (NAC...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Journal of the American Heart Association
Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high-risk population. Identifying reasons for statin nonuse, which are typically describ...

Detecting individuals with severe mental illness using artificial intelligence applied to magnetic resonance imaging.

EBioMedicine
BACKGROUND: Identifying individuals at risk for severe mental illness (SMI) is crucial for prevention and early intervention strategies. While MRI shows potential for case identification even before illness onset, no practical model for mental health...

An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.

Reproductive biomedicine online
RESEARCH QUESTION: Can a multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical parameters provide personalized evaluation of endometrial receptivity and predict the occurrence of clinical pregnancy after fr...

Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

Journal of digital imaging
The objective of this study is to develop a radiomic signature constructed from deep learning features and a nomogram for prediction of axillary lymph node metastasis (ALNM) in breast cancer patients. Preoperative magnetic resonance imaging data from...

Single-incision robotic colorectal surgery with the da Vinci SP® surgical system: initial results of 50 cases.

Techniques in coloproctology
PURPOSE: The da Vinci SP® (dVSP) surgical system (Intuitive Surgical, Sunnyvale, CA, USA), a robotic platform designed for single-incision surgery, overcame the need for multiple ports in traditional robotic surgery and issues including triangulation...

Incidental findings on CT scans for robot-assisted total joint arthroplasty.

ANZ journal of surgery
INTRODUCTION: This study documented the incidence of incidental findings from preoperative computerized-tomography (CT) scans obtained for robotic-arm-assisted total joint arthroplasty (TJA) and its effect on patient management.

Deep learning neural network image analysis of immunohistochemical protein expression reveals a significantly reduced expression of biglycan in breast cancer.

PloS one
New breast cancer biomarkers have been sought for better tumor characterization and treatment. Among these putative markers, there is Biglycan (BGN). BGN is a class I small leucine-rich proteoglycan family of proteins characterized by a protein core ...