Strengthening Artificial Intelligence Governance through Ethical Handling of Sensitive Data: An Applied Study on Text Classification and Differential Privacy

This research develops a comprehensive hybrid framework to enhance Artificial Intelligence governance by ethically managing sensitive textual data through advanced classification techniques. Focusing on natural language processing (NLP) applications, the study integrates rule-based systems, logistic regression, and transformer-based models, notably BERT, to address the challenges of identifying and handling sensitive information within complex and ambiguous linguistic contexts. Experimental results demonstrate that the hybrid model attains an overall classification accuracy of 91%, with precision and recall scores of 89% and 94%, respectively, achieving an F1-score of 92%. These metrics reflect the model’s robustness in real-world scenarios where explicit textual indicators are often lacking. Individually, the rule-based approach excels in precision (98.6%) for clearly identifiable sensitive content, logistic regression ensures perfect recall (100%), capturing all sensitive instances albeit with increased false positives, and the BERT model achieves perfect precision, effectively minimizing false alarms. The hybrid approach synergizes these strengths, resulting in a balanced and reliable classification system. The study further explores the integration of differential privacy via a differentially private logistic regression model using the diffprivlib library, assessing privacy-utility trade-offs at varying privacy budgets (ε = 3, 5, 6). Results reveal that stronger privacy guarantees (lower ε) reduce classification accuracy (78% at ε=3), while looser privacy constraints (ε=6) approach non-private model performance (97% accuracy). These findings underscore the potential of combining hybrid NLP models with differential privacy to deliver scalable, trustworthy, and privacy-preserving AI systems. The proposed framework holds significant relevance for sensitive domains such as healthcare, public administration, and corporate governance, where balancing data privacy and AI performance is critical. Future research should extend these findings by exploring additional privacy configurations and validating the approach against diverse real-world datasets to optimize the equilibrium between privacy protection and analytical effectiveness

Effect of nocturnal hypoxemia on glycemic control among diabetic Saudi patients presenting with obstructive sleep apnea

BackgroundObstructive sleep apnea (OSA) is a prevalent disease that is associated with an increased incidence of type II diabetes mellitus (DM) if left untreated. We aimed to determine the association between glycosylated hemoglobin (HbA1c) levels and both nocturnal hypoxemia and apnea-hypopnea index (AHI) among a Saudi patients with OSA.MethodsA cross-sectional study that enrolled 103 adult patients diagnosed with DM and confirmed to have OSA by full night attended polysomnography between 2018 and 2021. Those who presented with acute illness, chronic obstructive pulmonary disease (COPD)/restrictive lung diseases causing sleep-related hypoxemia, or no available HbA1c level within 6 months before polysomnography were excluded from the study. Univariate and multivariate linear regression analyses between HbA1c levels and parameters of interest were tested.ResultsSixty-seven (65%) of the studied population had uncontrolled DM (HbA1c ≥7%). In univariate regression analysis, there was a significant positive association between HbA1c, and sleep time spent with an oxygen saturation below 90% (T90), female gender, and body mass index (BMI) (p<0.05) but not AHI, or associated comorbidities (p>0.05). In the multivariate analysis, HbA1c was positively associated with increasing T90 (p<0.05), and ODI (p<0.05), but not with AHI (p>0.05).ConclusionNocturnal hypoxemia could be an important factor affecting glycemic control in patients with OSA suffering from DM irrespective of the severity of both diseases

The Saudi Critical Care Society practice guidelines on the management of COVID-19 in the ICU: Therapy section

BACKGROUND: The rapid increase in coronavirus disease 2019 (COVID-19) cases during the subsequent waves in Saudi Arabia and other countries prompted the Saudi Critical Care Society (SCCS) to put together a panel of experts to issue evidence-based recommendations for the management of COVID-19 in the intensive care unit (ICU). METHODS: The SCCS COVID-19 panel included 51 experts with expertise in critical care, respirology, infectious disease, epidemiology, emergency medicine, clinical pharmacy, nursing, respiratory therapy, methodology, and health policy. All members completed an electronic conflict of interest disclosure form. The panel addressed 9 questions that are related to the therapy of COVID-19 in the ICU. We identified relevant systematic reviews and clinical trials, then used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach as well as the evidence-to-decision framework (EtD) to assess the quality of evidence and generate recommendations. RESULTS: The SCCS COVID-19 panel issued 12 recommendations on pharmacotherapeutic interventions (immunomodulators, antiviral agents, and anticoagulants) for severe and critical COVID-19, of which 3 were strong recommendations and 9 were weak recommendations. CONCLUSION: The SCCS COVID-19 panel used the GRADE approach to formulate recommendations on therapy for COVID-19 in the ICU. The EtD framework allows adaptation of these recommendations in different contexts. The SCCS guideline committee will update recommendations as new evidence becomes available

Diagnosis and Fault Detection of Rotor Bars in Squirrel Cage Induction Motors Using Combined Park’s Vector and Extended Park’s Vector Approaches

The induction motor (IM) is considered to be one of the most important types of motors used in industries. A sudden failure in this machine can lead to unwanted downtime, with consequences in costs, product quality, and safety. Over the last decade, several methods and techniques have been proposed to diagnose and detect faults in induction machines. In this paper, we present the development of a new algorithm based on the combination of both the Park’s vector approach (PVA) and the extended Park’s vector approach (EPVA) for broken rotor bars (BRBs) fault detection and identification. This fault can be detected using the PVA by monitoring the thickness and orientation of the park’s vector pattern and using EPVA by identifying specific spectral components related to the fault. For ability evaluation of our suggested algorithm, simulations and experiments are conducted and presented. The obtained results demonstrate that the proposed algorithm is accurate and effective and can be extensively used in IM fault detections and identifications.</jats:p

Assessment of Primary Care Physicians&rsquo; Expertise of Common Dermatological Conditions in the Jouf Region, Saudi Arabia: A Mixed Methods Study

Primary care physicians (PCPs) are the first line of defense for the management of common dermatological conditions (DCs). This study aimed to assess how dermatological diseases are identified, managed, and referred to in primary healthcare centers (PHCs). This was a mixed methods study comprising a cross-sectional survey and semi-structured interviews recruited through PHCs across the Jouf region of Saudi Arabia. Sixty-one PCPs completed the data, and eight participants were interviewed. A survey based on a sample of 22 photographs of common DCs in the Kingdom was administered to the participants to answer questions about the correct diagnosis, appropriate management, referral strategy, and encounter rate. In our sampled population, the mean overall knowledge level on a scale of 10 was 7.08 (&plusmn;1.3). Among participants that had good to acceptable scores, 51 (83.6%) were in the overall knowledge parameter, 46 (75.4%) in the diagnosis parameter, and 49 (80.3%) in the management parameter. PCPs with five years or more of experience were found to have significantly higher overall knowledge and management scores. Most of our PCPs demonstrated sufficient knowledge of common DCs and had good to acceptable scores in all parameters. However, educational and regulatory aspects of PCPs&rsquo; clinical management were identified. Focused training, provision of workshops, and improving medical school curricula regarding common DCs are recommended

Causes and Management of Acute Pyelonephritis

Acute pyelonephritis is a bacterial infection that causes kidney inflammation. Pyelonephritis is a kidney infection that develops as a result of an ascending urinary tract infection that travels from the bladder to the kidneys. Acute pyelonephritis affects over 250,000 people each year, resulting in more than 100,000 hospitalizations. Infection with Escherichia coli is the most prevalent cause. Fever, vomiting, abdomen or loin discomfort, and fatigue are all symptoms of acute pyelonephritis, however Fever is the most clinically useful symptom. Escherichia coli is the causative agent in more than 80% of instances of acute pyelonephritis. Staphylococcus saprophyticus, and enterococci are among the other etiologic factors. While Infections caused by Klebsiella, Enterobacter, Clostridium, or Candida are more common in diabetic patients. Acute pyelonephritis can be treated as an outpatient or as an inpatient procedure. Outpatient treatment is available for healthy, young, non-pregnant women with uncomplicated pyelonephritis. The choice of first-line oral antibiotics depends on local antibiotic resistance characteristics, although trimethoprim alone or in combination with sulphamethoxazole, cephalexin, or amoxicillin-clavulanic acid. In this article we will be looking the causes and management of acute pyelonephritis.</jats:p

Effect of nocturnal hypoxemia on glycemic control among diabetic Saudi patients presenting with obstructive sleep apnea

BackgroundObstructive sleep apnea (OSA) is a prevalent disease that is associated with an increased incidence of type II diabetes mellitus (DM) if left untreated. We aimed to determine the association between glycosylated hemoglobin (HbA1c) levels and both nocturnal hypoxemia and apnea-hypopnea index (AHI) among a Saudi patients with OSA.MethodsA cross-sectional study that enrolled 103 adult patients diagnosed with DM and confirmed to have OSA by full night attended polysomnography between 2018 and 2021. Those who presented with acute illness, chronic obstructive pulmonary disease (COPD)/restrictive lung diseases causing sleep-related hypoxemia, or no available HbA1c level within 6 months before polysomnography were excluded from the study. Univariate and multivariate linear regression analyses between HbA1c levels and parameters of interest were tested.ResultsSixty-seven (65%) of the studied population had uncontrolled DM (HbA1c ≥7%). In univariate regression analysis, there was a significant positive association between HbA1c, and sleep time spent with an oxygen saturation below 90% (T90), female gender, and body mass index (BMI) (p&amp;lt;0.05) but not AHI, or associated comorbidities (p&amp;gt;0.05). In the multivariate analysis, HbA1c was positively associated with increasing T90 (p&amp;lt;0.05), and ODI (p&amp;lt;0.05), but not with AHI (p&amp;gt;0.05).ConclusionNocturnal hypoxemia could be an important factor affecting glycemic control in patients with OSA suffering from DM irrespective of the severity of both diseases.</jats:sec

DataSheet_1_Effect of nocturnal hypoxemia on glycemic control among diabetic Saudi patients presenting with obstructive sleep apnea.docx

BackgroundObstructive sleep apnea (OSA) is a prevalent disease that is associated with an increased incidence of type II diabetes mellitus (DM) if left untreated. We aimed to determine the association between glycosylated hemoglobin (HbA1c) levels and both nocturnal hypoxemia and apnea-hypopnea index (AHI) among a Saudi patients with OSA.MethodsA cross-sectional study that enrolled 103 adult patients diagnosed with DM and confirmed to have OSA by full night attended polysomnography between 2018 and 2021. Those who presented with acute illness, chronic obstructive pulmonary disease (COPD)/restrictive lung diseases causing sleep-related hypoxemia, or no available HbA1c level within 6 months before polysomnography were excluded from the study. Univariate and multivariate linear regression analyses between HbA1c levels and parameters of interest were tested.ResultsSixty-seven (65%) of the studied population had uncontrolled DM (HbA1c ≥7%). In univariate regression analysis, there was a significant positive association between HbA1c, and sleep time spent with an oxygen saturation below 90% (T90), female gender, and body mass index (BMI) (p0.05). In the multivariate analysis, HbA1c was positively associated with increasing T90 (p0.05).ConclusionNocturnal hypoxemia could be an important factor affecting glycemic control in patients with OSA suffering from DM irrespective of the severity of both diseases.</p