This section focuses on recent global studies and discoveries in the various fields of healthcare.
Artificial intelligencebased radiomic approaches have been shown to accurately evaluate indeterminate pulmonary nodules With the expansion of lung cancer screening and utilization of computed tomography imaging
Machine learning ML algorithms are increasingly used in healthcare to support clinical decisionmaking While models with similar overall performance are often considered interchangeable for deployment
COVID an unprecedented global pandemic has caused successive waves that pose unique challenges to public health and epidemiological research Traditional SusceptibleInfectedRecovered SIR models often struggle to capture these complex dynamics
Radical resection of bone tumors is a clinically effective but costly procedure Despite the implementation of federal price transparency mandates little is known about the nationwide variation in negotiated prices for these specialized oncologic surgeries
Postoperative outcomes of cardiovascular surgery vary greatly among patients for a variety of reasons
Pediatric traumatic brain injury often leads to longterm disability Unfortunately while currently used standard clinical measures can effectively
Patients with cancer who develop acute abdomen are at high risk of rapid clinical deterioration and often require emergency surgery and intensive care This retrospective cohort study evaluated
Glaucoma is an optic neuropathy characterized by progressive retinal ganglion cells degeneration and associated visual field defects Although elevated intraocular pressure is a major risk factor
Texture analysis is a foundational approach in imaging studies and demonstrates excellent diagnostic performance with radiomic analysis being the most widely used method
The incidence of allergic rhinitis AR has been increasing annually severely impacting patients quality of life and increasing socioeconomic burdens The limitations of current diagnostic methods
