Detecting anomalies in smart wearables for hypertension: a deep learning mechanism.

Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).

Recognition of diabetic retinopathy and macular edema using deep learning.

Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual image analysis by experts, which can be time-consuming and costly due to the scarcity of such experts. To overcome the aforementioned challenges, we present the Modified CornerNet approach with DenseNet-100.

Pandemic disease detection through wireless communication using infrared image based on deep learning.

Rapid diagnosis to test diseases, such as COVID-19, is a significant issue. It is a routine virus test in a reverse transcriptase-polymerase chain reaction. However, a test like this takes longer to complete because it follows the serial testing method, and there is a high chance of a false-negative ratio (FNR).

Breast Arterial Calcifications: Reporting Preferences and Impact on Screening for Coronary Artery Disease.

Objective: Breast arterial calcifications (BAC) have been shown to correlate with measures of coronary artery disease risk stratification, although reporting of BAC is optional by BI-RADS guidelines. The purpose of this study is to determine referring provider preferences in BAC reporting on mammography reports and if such reporting has any impact on patient management.

Methods: This study was approved by the local institutional review board.

Spilled stones following pyelolithotomy: An unusual mimic of peritoneal carcinomatosis.

While spillage of intraperitoneal gallstones has been reported frequently in the literature, spilled renal stones after urologic intervention is rare. The dropped renal stones may mimic peritoneal carcinomatosis (PC) on imaging, causing concern and potentially leading to unnecessary diagnostic workup. Additionally, these dropped stones may cause surrounding inflammation, potentially leading to the formation of adhesions or an intra-abdominal abscess.

Asymptomatic pneumoperitoneum in the setting of pneumatosis intestinalis: a benign entity or surgical emergency?

Pneumatosis intestinalis is a potential cause of asymptomatic pneumoperitoneum without peritonitis. The disease can be managed conservatively and presents a clinical scenario where pneumoperitoneum does not necessitate surgical management. This case illustrates the importance of acknowledging the condition and its variable presentation, allowing for increased awareness and avoidance of invasive procedures when not indicated.

Atypical Mixed Variant of Pericallosal Lipoma With Splenial Dysgenesis.

Pericallosal lipomas are rare benign intracranial masses that arise during embryonic development, typically categorized into tubulonodular and curvilinear subtypes. A mixed variant of both tubulonodular and curvilinear subtypes is very rare. Patients with pericallosal lipomas may be asymptomatic or may have different presentations, such as headaches.

Idiopathic Mandibular Condyle Resorption.

Idiopathic mandibular condylar resorption is a rare condition in which the mandibular condyle of the temporomandibular joint (TMJ) becomes resorbed and thus reduces in size and volume. This leads to TMJ dysfunction that commonly requires surgical correction; however, more conservative interventions can also be utilized. We present a case of idiopathic mandibular condyle resorption in a 17-year-old female presenting with TMJ pain and clicking with mastication.