Machine learning, a branch of artificial intelligence, is increasingly used in health research, including nursing and maternal outcomes research. Machine learning algorithms are complex and involve statistics and terminology that are not common in he...
This study analyzed the prognostic significance of clinico-pathologic factors, including the number of metastatic lymph nodes (LNs) and lymph node ratio (LNR), in patients with papillary thyroid carcinoma (PTC), and attempted to construct a disease r...
BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.
BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences f...
BACKGROUND: There are no established accurate models that use machine learning (ML) methods to preoperatively predict immediate remission after transsphenoidal surgery (TSS) in patients diagnosed with histology-positive Cushing's disease (CD).
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 2, 2021
Ataxic gait monitoring and assessment of neurological disorders belong to important multidisciplinary areas that are supported by digital signal processing methods and machine learning tools. This paper presents the possibility of using accelerometri...
Frontiers in cellular and infection microbiology
Mar 2, 2021
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients' condition. We...
IMPORTANCE: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve compariso...
IMPORTANCE: Cervical cancer is highly preventable but remains a common and deadly cancer in areas without screening programs. The creation of a diagnostic system to digitize Papanicolaou test samples and analyze them using a cloud-based deep learning...
IMPORTANCE: Before the widespread implementation of robotic systems to provide patient care during the COVID-19 pandemic occurs, it is important to understand the acceptability of these systems among patients and the economic consequences associated ...
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