FacialNet: facial emotion recognition for mental health analysis using UNet segmentation with transfer learning model.

Facial emotion recognition (FER) can serve as a valuable tool for assessing emotional states, which are often linked to mental health. However, mental health encompasses a broad range of factors that go beyond facial expressions. While FER provides insights into certain aspects of emotional well-being, it can be used in conjunction with other assessments to form a more comprehensive understanding of an individual's mental health.

Early detection of autism spectrum disorder using explainable AI and optimized teaching strategies.

Autism spectrum disorder (ASD) is defined by the deficits of social relating, language, object use and understanding, intelligence and learning, and verbal and nonverbal communication. Most of the individuals with ASD have genetic conditions; however, early identification and intervention reduce the use of health services and other diagnostic procedures. The varied nature of ASD is widely acknowledged, with each affected individual displaying distinct traits.

Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence.

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable challenges in cognitive function, understanding language, recognizing objects, interacting with others, and communicating effectively. Its origins are mainly genetic, and identifying it early and intervening promptly can reduce the necessity for extensive medical treatments and lengthy diagnostic procedures for those impacted by ASD. This research is designed with two types of experimentation for ASD analysis.

Spatio-temporal soil loss modelling using RUSLE and sediment delivery into a reservoir in a semi-arid region of northern Nigeria.

Soil loss is aggravated by uncontrolled deforestation, indiscriminate land clearing for agricultural activities, overgrazing, and urban development that leads to severe soil erosion over the land surface. The main objective of this research is to apply the Revised Universal Soil Loss Equation (RUSLE), in conjunction with remote sensing and GIS, to determine the temporal variation of soil loss from the Gubi watershed in the years 2000 and 2017 and to estimate the sediment delivery into the Gubi reservoir in Northern Nigeria. Datasets of rainfall, soil type, topography, cover management, and support practice were utilized to determine the five RUSLE factors.

Artificial intelligence-driven predictive framework for early detection of still birth.

Predictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. Stillbirth prediction is a similar domain where artificial intelligence-based predictive modeling can alleviate this significant global health challenge.

Colloidal 2D Layered SiC Quantum Dots from a Liquid Precursor: Surface Passivation, Bright Photoluminescence, and Planar Self-Assembly.

We report the bottom-up synthesis of colloidal two-dimensional (2D) layered silicon carbide (SiC) quantum dots with a cubic structure, lateral size of 5-10 nm, ⟨110⟩ exfoliation to few atomic layers, and surface passivation with 1-dodecene. Samples shielded from oxygen and plasma-annealed for purity exhibit narrow blue photoluminescence (PL) with quantum yields (QYs) over 60% in exceptional cases, while unshielded nanocrystals (NCs) exhibit broad blue/green/white PL with 10-15% QY. The latter scenario is attributed to excess surface carbon and oxygen accrued during synthesis and processing, with size separation through ultracentrifugation revealing size-dependent impurity emission.

Robotic and Laparoscopic Adrenalectomy for Pheochromocytoma: An International Multicenter Study.

Background And Objective: Robotic adrenalectomy (RA) has attracted interest as an alternative to laparoscopic adrenalectomy (LA) for patients with pheochromocytoma, although its beneficial effects are uncertain. Our aim was to compare RA and LA outcomes for these patients.

Methods: Data for patients who underwent RA or LA for pheochromocytoma in 46 international centers between 2012 and 2022 were reviewed.

Machine learning predictive insight of water pollution and groundwater quality in the Eastern Province of Saudi Arabia.

This study presents an innovative approach for predicting water and groundwater quality indices (WQI and GWQI) in the Eastern Province of Saudi Arabia, addressing critical challenges of scarcity and pollution in arid regions. Recent literature highlights the increasing attention towards WQI based on water pollution index (WPI) and GWQI as essential tools for simplifying complex hydrogeological data, thereby facilitating effective groundwater management and protection. Unlike previous works, the present research introduces a novel hybrid method that integrates non-parametric kernel Gaussian learning (GPR), adaptive neuro-fuzzy inference system (ANFIS), and decision tree (DT) algorithms.

Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization.

The rising heavy metal (HM) pollution in coastal aquifers in rapidly urbanizing areas such as Dammam leads to significant risks to public health and environmental sustainability, challenging compliance with Environmental Protection Agency (EPA) guidelines, World Health Organization (WHO) standards, and Sustainable Development Goals (SDGs) related to clean water and life on land. This study developed the predictive-based monitoring of HM concentrations, including cadmium (Cd), chromium (Cr), and mercury (Hg) in the coastal aquifers of Dammam, influenced by industrial, agricultural, and urban activities. For this purpose, dynamic system identification and machine learning (ML) models integrated with three ensemble techniques, namely, simple averaging (SAE), weighted averaging (WAE), and neuro-ensemble (N-ESB), were employed to enhance the accuracy, reliability, and efficiency of environmental monitoring systems.

Comparative efficacy of digital panoramic radiograph and cone beam computed tomography in locating mandibular foramen.

Objective: The aim of this study was to compare the accuracy of panoramic radiographs (PAN) with cone-beam computed tomography (CBCT) in locating the position of the mandibular foramen (MF).

Patients And Methods: A total of 100 patients who underwent CBCT and panoramic imaging were included in the study. The location of the MF was evaluated anterior-posteriorly and superior-inferiorly on both CBCT and panoramic radiographs.

The Role of Therapeutic Drug Monitoring in Slow Response Extra-Pulmonary Tuberculosis Treatment: A Case Report.

Tuberculosis is caused by an infectious bacterium and it has significant morbidity and mortality rates globally. It mostly affects the lungs, but it can also spread to other parts of the body, like the lymph nodes (tuberculous lymphadenitis). The most common way to treat it is with the RIPE regimen, which includes rifampin, isoniazid, pyrazinamide, and ethambutol.

Effectiveness of Telemedicine in Controlling Hyperglycemia Among Diabetic Patients on Insulin Therapy in Primary Care: A Systematic Review and Meta-Analysis.

This study investigates the effectiveness of telemedicine in managing glucose levels in insulin-treated diabetes patients compared to standard care. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) criteria and Cochrane's risk of bias tool, an analysis of five selected studies reveals telemedicine as a potent tool in diabetes management. Fasting blood sugar (FBS) test results from two studies involving an eight-hour fast with 109 participants demonstrate a significant superiority of telemedicine over usual care (Tau2 = 1.

Risk factors for postoperative complications after adrenalectomy for phaeochromocytoma: multicentre cohort study.

Background: To determine the incidence and risk factors for postoperative complications and prolonged hospital stay after adrenalectomy for phaeochromocytoma.

Methods: Demographics, perioperative outcomes and complications were evaluated for consecutive patients who underwent adrenalectomy for phaeochromocytoma from 2012 to 2020 in nine high-volume UK centres. Odds ratios were calculated using multivariable models.

Risk factors for postoperative hypotension after adrenalectomy for phaeochromocytoma: derivation of the PACS risk score.

Background: Due to the risk of postoperative hypotension (PH), invasive monitoring is recommended for patients who undergo adrenalectomy for phaeochromocytoma. Due to high costs and limited availability of intensive care, our aim was to identify patients at low risk of PH who may not require invasive monitoring.

Methods: Data for patients who underwent adrenalectomy for phaeochromocytoma between 2012 and 2020 were retrospectively collected by nine UK centres, including patient demographics, intraoperative and postoperative haemodynamic parameters.

Prediction of sustainable management of sediment in rivers and reservoirs.

Water structure construction has been the subject of heated discussion for more than a decade. The following concepts include integrated management of water basins or continued sustainable development of water basins. Although there are not a lot of underdeveloped water basins, there have been 150 years of dam development.

Online family medicine training amid the COVID-19 crisis in KSA: A mixed-method study.

Objective: Literature on the perceptions and experiences of postgraduate trainees and trainers regarding online methods of learning is scarce. We aimed to assess the perceptions and experiences of family medicine trainees and trainers regarding online learning during the novel coronavirus (COVID-19) pandemic in Qassim, KSA.

Methods: This was a mixed-method study involving trainees and trainers at the Family Medicine Academy, Qassim.

Evaluating the Inappropriate Prescribing and Utilization of Caspofungin, a Four-Year Analysis at a Teaching Hospital in Saudi Arabia.

The appropriate use of antimicrobial agents improves clinical outcomes and reduces antimicrobial resistance. Nevertheless, data on inappropriate prescription and negative outcomes are inconsistent. The objective of this study was to assess the prescription appropriateness of Caspofungin at a tertiary teaching hospital in Saudi Arabia and the impact on mortality at 30 days.

Factors associated with poor outcomes among hospitalized patients with COVID-19: Experience from a MERS-CoV referral hospital.

Background: Coronavirus disease 2019 (COVID-19) has resulted in millions of deaths, including more than 6000 deaths in the Kingdom of Saudi Arabia (KSA). Identifying key predictors of intensive care unit (ICU) admission and mortality among infected cases would help in identifying individuals at risk to optimize their care. We aimed to determine factors of poor outcomes in hospitalized patients with COVID-19 in a large academic hospital in Riyadh, KSA that serves as a Middle East Respiratory Syndrome coronavirus (MERS-CoV) referral center.

Clinical characteristics and outcomes of hospitalized COVID-19 patients in a MERS-CoV referral hospital during the peak of the pandemic.

Objective: To describe the clinical characteristics and outcomes of hospitalized coronavirus disease 2019 (COVID-19) patients in a middle east respiratory syndrome coronavirus (MERS-CoV) referral hospital during the peak months of the pandemic.

Design: A single-center case series of hospitalized individuals with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in King Saud University Medical City (KSUMC), an academic tertiary care hospital in Riyadh, Saudi Arabia. Clinical and biochemical markers were documented.

Psychological impact of the coronavirus disease 2019 (COVID-19) pandemic on dental students: A nationwide study.

Objectives: Public mental health concerns have been raised during the coronavirus disease 2019 (COVID-19) pandemic. The aim of this study was to assess the psychological impact of the pandemic on dental students in Saudi Arabia.

Methods: A cross-sectional analytical study was conducted among dental students from different universities in Saudi Arabia selected using 2-stage cluster sampling.

Does Being Transported by Emergency Medical Services Improve Compliance with the Surviving Sepsis Bundle and Mortality Rate? A Retrospective Cohort Study.

Background: This study aimed to investigate the relationship between patients with severe sepsis or septic shock being transported to the Emergency Department (ED) by Emergency Medical Services (EMS) and the compliance with the 3-h sepsis resuscitation bundle [Surviving Sepsis Campaign (SSC)], and to compare the management and laboratory results of patients transported by EMS or non-EMS transport.

Methods: A retrospective cohort study was conducted using data from a quality-improvement project at King Abdulaziz Medical City in Riyadh. The data for patients who presented to ED with sepsis (severe sepsis or septic shock) was categorized as being transported with EMS or non-EMS.

Streptococcus anginosus group infections: Management and outcome at a tertiary care hospital.

Background: Data on patients with invasive Streptococcus anginosus group (SAG) infections is limited, as it's been considered commensal bacteria in the human microbiota. We conducted an analysis of SAG infections to assist clinicians in understanding their burden and clinical outcomes.

Methods: A retrospective study of medical records, identifying invasive SAG bacteria of sterile-site isolates that were managed from May 2015 to April 2017, at a tertiary care hospital in Riyadh, Saudi Arabia.