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mahardika
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p3i@umsida.ac.id
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6285159046771
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anamnetic@umsida.ac.id
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jl. Mojopahit no.666B Sidoarjo, Jawa Timur
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Kab. sidoarjo,
Jawa timur
INDONESIA
Journal of Medical and Health Science
Published by Universitas Muhammadiyah Sidoarjo
ISSN : -     EISSN : 30321182     DOI : https://doi.org/10.21070/anamnetic
Core Subject : Health, Science,
Decision Sciences, Operations Research & Management Health Professions Medicine & Pharmacology Public Health
Focus: Journal of Medical and Health Science aims to communicate the research results of professors, teachers, practitioners, and scientists in the fields of health information management and health science. The journal provides a platform for sharing significant and innovative findings that contribute to the advancement of these areas. Scope: The journal covers a wide range of topics within health information management and health science, including but not limited to: Health Information Management: Systems and technologies for managing health information Health data analytics and informatics Electronic health records and health information systems Medical Sciences: Clinical research and medical advancements Diagnostics and treatment methodologies Biomedical research and innovations Pharmacy: Pharmaceutical sciences and drug development Pharmacology and therapeutics Pharmacy practice and medication management Public Health: Epidemiology and public health policies Health promotion and disease prevention Community health initiatives and programs Environmental Health: Impact of environmental factors on health Environmental health risk assessment Strategies for environmental health improvement Midwifery: Maternal and child health care practices Midwifery education and training Innovations in prenatal and postnatal care Nursing: Nursing practices and patient care Nursing education and professional development Research in nursing and healthcare outcomes Other Health Professionals: Interdisciplinary research involving various health professionals Health services management and policy Innovations in healthcare delivery and practice
Arjuna Subject : Profesi Kesehatan - Menejmen Informasi Kesehatan
Articles 43 Documents
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Association of Toxoplasma gondii Seropositivity and TNF-α -308G/A Polymorphism with Type 2 Diabetes Mellitus in Women Al-Kalabi, Firas Kareem Al-Kalabi
JOURNAL OF MEDICAL AND HEALTH SCIENCE Vol. 4 No. 1 (2026): July
Publisher : Universitas Muhammadiyah Sidaorjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/anamnetic.v4i1.1646

Abstract

General Background: Type 2 Diabetes Mellitus (T2DM) is a multifactorial metabolic disorder involving genetic and environmental components with chronic low-grade inflammation. Specific Background: Infectious agents such as Toxoplasma gondii and inflammatory cytokine gene variations, including TNF-α -308G/A polymorphism, have been investigated for their association with metabolic disturbances. Knowledge Gap: The combined relationship between T. gondii seropositivity and TNF-α genetic variation in women with T2DM remains insufficiently characterized. Aims: This study aimed to evaluate the association of T. gondii infection and TNF-α -308G/A polymorphism with T2DM in women. Results: In a case-control design involving 480 women, T2DM cases showed higher T. gondii IgG seropositivity (68.3% vs. 45.8%) and elevated IgG titers (47.3 ± 28.6 vs. 32.1 ± 24.8 IU/mL). Additionally, the A allele frequency of TNF-α -308G/A was higher in cases than controls (0.256 vs. 0.208; OR = 1.31, P = 0.047). Novelty: This study integrates parasitic infection status with inflammatory genetic polymorphism in a single analytical framework among women. Implications: Findings suggest that chronic infection and genetic susceptibility are associated with T2DM, supporting further investigation into inflammatory and infectious pathways in metabolic disorders. Highlights:• Higher IgG seroprevalence observed among diabetic participants• Elevated antibody titers indicate persistent parasitic exposure patterns• Allelic variation linked with increased disease susceptibility Keywords: Toxoplasma Gondii, Type 2 Diabetes Mellitus, TNF Alpha Polymorphism, Seropositivity, Case Control Study
The digital revolution in medical imaging: The Role of artificial intelligence (AI) in the future of radiology: A subject review Duraid Manea Bashara; Fathinul Fikri Ahmed Saad
JOURNAL OF MEDICAL AND HEALTH SCIENCE Vol. 4 No. 1 (2026): July
Publisher : Universitas Muhammadiyah Sidaorjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/anamnetic.v4i1.1655

Abstract

General Background: Radiology has evolved from analog image interpretation to data-intensive digital analysis, creating opportunities for artificial intelligence (AI) to support diagnostic and operational processes. Specific Background: AI, particularly deep learning and convolutional neural networks, is increasingly applied in lesion detection, image segmentation, image reconstruction, workflow triage, and radiomics. Knowledge Gap: Despite rapid adoption, a comprehensive synthesis of AI applications in radiology and the associated technical, ethical, and legal barriers remains necessary. Aims: This review examines current AI applications in medical imaging, their role in precision medicine, and the major challenges affecting clinical implementation. Results: AI demonstrated expert-level performance in detecting pulmonary nodules, breast cancer, and pancreatic lesions; automated segmentation improved quantitative assessment of tumors and neurodegenerative changes; deep learning reconstruction reduced radiation dose and shortened MRI acquisition time; triage systems prioritized urgent findings and reduced turnaround time; and radiomics and radiogenomics enabled non-invasive “virtual biopsy” and prognostic modeling. Novelty: This review integrates diagnostic, operational, and predictive roles of AI across the entire radiology workflow within the concept of augmented intelligence. Implications: AI is positioned as a collaborative tool that supports radiologists and advances precision medicine, while successful adoption depends on explainability, data generalizability, privacy protection, and clear regulatory frameworks. Highlights: • AI supports lesion detection, segmentation, and image reconstruction in medical imaging.• Intelligent triage and scheduling reduce turnaround time and improve radiology workflow.• Radiomics and radiogenomics enable non-invasive tumor characterization and prognosis prediction. Keywords: Artificial Intelligence, Radiology, Deep Learning, Radiomics, Precision Medicine  
Progressive Worsening of Vitamin D Deficiency Is Associated With Adverse Clinical Outcomes in Surgical Intensive Care Unit Patients Ahmed Bassam Rasheed; Zahraa Kamil Yousif; Ahmed Amer Abdulhussein; Marwah Mohammed Qasim; Ahmed Hashim Hammoodi
JOURNAL OF MEDICAL AND HEALTH SCIENCE Vol. 4 No. 1 (2026): July
Publisher : Universitas Muhammadiyah Sidaorjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/anamnetic.v4i1.1654

Abstract

General Background: Vitamin D deficiency is recognized as a major nutritional disorder associated with immune dysregulation, prolonged hospitalization, and increased mortality in critically ill populations. Specific Background: Surgical intensive care unit (SICU) patients are particularly vulnerable to hypovitaminosis D because of severe physiological stress, limited nutritional intake, and reduced sunlight exposure during hospitalization. Knowledge Gap: Despite increasing evidence linking vitamin D deficiency with adverse outcomes, limited prospective data are available regarding the severity distribution and prognostic significance of vitamin D deficiency among surgical ICU patients in Iraq. Aims: This study evaluated the prevalence of vitamin D deficiency and its association with clinical outcomes among SICU patients admitted to Ghazi AL Hariri Hospital for Surgical Specialties, Baghdad. Results: A prospective cohort study involving 240 SICU patients demonstrated that severe vitamin D deficiency was present in 53.5% of participants, while only 1.2% had normal vitamin D status. Severe deficiency was associated with prolonged SICU stay, increased treatment costs, and higher mortality rates. Patients with severe deficiency showed a mean SICU stay of 15.33 days, significantly longer than those with moderate or mild deficiency (P = 0.002). Multivariate analysis confirmed vitamin D deficiency as an independent predictor of adverse clinical outcomes. Novelty: The study introduces severity-based vitamin D classification in SICU patients and demonstrates its prognostic relevance in a critically ill surgical population. Implications: Early screening and correction of vitamin D deficiency may support risk stratification and clinical management strategies in surgical intensive care settings. Highlights: • Severe hypovitaminosis D predominated among critically ill surgical patients admitted to SICU.• Longer intensive care hospitalization was identified in patients with profound nutrient depletion.• Mortality and treatment expenditure increased across lower serum 25-hydroxyvitamin D categories. Keywords: Vitamin D Deficiency, Surgical Intensive Care Unit, Critical Illness, Mortality, Serum 25 Hydroxyvitamin D

Page 5 of 5 | Total Record : 43

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