Latest AI and machine learning research in us health policy for healthcare professionals.
Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and act upon the predictions made with ML, more intuitive user interfaces must be validated. Thus, Interpretable AI is one of the crucial directions which c...
This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms of Alzheimer's disease and related dementias (ADRD) documented in clinicians' free-text notes; (2) determine whether signs and symptoms detected via NLP help to identify patients at risk of a new ADRD diagnosis within four years after admission. Thi...
The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derive...
Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convo...
Medical devices have increased in complexity where there is a pressing need to consider design thinking and specialist training for manufacturers, hea...
Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models ...
Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the most reliable way to prevent oral cancer. Computational ...
The influence of Medicaid or being uninsured is prevailingly thought to negatively impact a patient's socioeconomic and postoperative course, yet litt...
Neurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain h...
ICU readmissions are associated with poor outcomes for patients and poor performance of hospitals. Patients who are readmitted have an increased risk ...
Common scab (CS) is a major bacterial disease causing lesions on potato tubers, degrading their appearance and reducing their market value. To accurat...
To investigate the effectiveness of continuity of care after robot-assisted adrenal tumor resection under ambulatory mode. Patients who underwent robo...
Multiple applications for machine learning and artificial intelligence (AI) in cardiovascular imaging are being proposed and developed. However, the p...
Utilising three artificial intelligence (AI)/machine learning (ML) tools, this study explores the prediction of fill level in inclined linear blenders...
Participatory data stewardship (PDS) empowers individuals to shape and govern their data via responsible collection and use. As artificial intelligenc...
OBJECTIVE: To estimate the therapeutic inertia prevalence for patients with type 2 diabetes, develop and validate a machine learning model predicting ...
Lower limb exoskeletons and orthoses have been increasingly used to assist the user during gait rehabilitation through torque transmission and motor s...
This study aimed to explore the correlation between serum creatinine and burn severity and the value of predicting the outcome of patients. For this p...
BACKGROUND: T-wave alternans (TWA) analysis was shown in >14,000 individuals studied worldwide over the past two decades to be a useful tool to assess...
In the mid-twentieth century, the social movement of death revivalism sought to resist the medicalisation of dying and grief through promotion of the ...