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Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.

Frontiers in immunology
INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome coronavirus 2 is alarmingly high. This study aimed to explore the predictive value of a novel model for assessing the risk of death in this vulnerable...

Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data.

Frontiers in public health
BACKGROUND: Chronic kidney disease (CKD) is characterized by a decreased glomerular filtration rate or renal injury (especially proteinuria) for at least 3 months. The early detection and treatment of CKD, a major global public health concern, before...

ACL-DUNet: A tumor segmentation method based on multiple attention and densely connected breast ultrasound images.

PloS one
Breast cancer is the most common cancer in women. Breast masses are one of the distinctive signs for diagnosing breast cancer, and ultrasound is widely used for screening as a non-invasive and effective method for breast examination. In this study, w...

Unsupervised learning for real-time and continuous gait phase detection.

PloS one
Individuals with lower limb impairment after a stroke or spinal cord injury require rehabilitation, but traditional methods can be challenging for both patients and therapists. Robotic systems have been developed to help; however, they currently cann...

A novel meta learning based stacked approach for diagnosis of thyroid syndrome.

PloS one
Thyroid syndrome, a complex endocrine disorder, involves the dysregulation of the thyroid gland, impacting vital physiological functions. Common causes include autoimmune disorders, iodine deficiency, and genetic predispositions. The effects of thyro...

Comparison of deep learning approaches to estimate injury severity from the International Classification of Diseases codes.

Traffic injury prevention
OBJECTIVE: The injury severity classification based on the Abbreviated Injury Scale (AIS) provides information that allows for standardized comparisons for injury research. However, the majority of injury data is captured using the International Clas...

Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study.

Journal of stomatology, oral and maxillofacial surgery
OBJECTIVE: The purpose of this study was to investigate the diagnostic performance of a neural network Artificial Intelligence model for the radiographic confirmation of Temporomandibular Joint Osteoarthritis in reference to an experienced radiologis...

Applying Deep-Learning Algorithm Interpreting Kidney, Ureter, and Bladder (KUB) X-Rays to Detect Colon Cancer.

Journal of imaging informatics in medicine
Early screening is crucial in reducing the mortality of colorectal cancer (CRC). Current screening methods, including fecal occult blood tests (FOBT) and colonoscopy, are primarily limited by low patient compliance and the invasive nature of the proc...

Automated speech recognition bias in personnel selection: The case of automatically scored job interviews.

The Journal of applied psychology
Organizations, researchers, and software increasingly use automatic speech recognition (ASR) to transcribe speech to text. However, ASR can be less accurate for (i.e., biased against) certain demographic subgroups. This is concerning, given that the ...