cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Aen Fariah
Contact Email
aenfariah1995@gmail.com
Phone
+6282214018102
Journal Mail Official
healthsains@gmail.com
Editorial Address
http://jurnal.healthsains.co.id/index.php/jhs/about/editorialTeam
Location
Kota cirebon,
Jawa barat
INDONESIA
Jurnal Health Sains
Published by Syntax Corporation Indonesia
ISSN : 27236927     EISSN : 27234339     DOI : http://doi.org/10.36418
Core Subject : Health,
Dentistry Health Professions Medicine & Pharmacology Nursing Public Health Veterinary
Jurnal Health Sains adalah jurnal yang diterbitkan sebulan sekali oleh Ridwan Institute. Jurnal Health Sains akan menerbitkan artikel ilmiah dalam lingkup ilmu kesehatan. Artikel yang diterbitkan adalah artikel dari penelitian, studi atau studi ilmiah kritis dan komprehensif tentang isu-isu penting dan terkini atau ulasan buku-buku ilmiah.
Arjuna Subject : Profesi Kesehatan - Bimbingan Kesehatan dan Transkripsi
Articles 783 Documents
 75   76   77   78   79 
A Comparison of Recist 1.1 and the Side Effects of Neoadjuvant Chemotherapy Based on Anthracyclines and Taxane in Patients with Advanced Local-Stage Breast Cancer at Prof. Dr. R.D. Kandou General Hospital Toby Hadinata Wiranegara; Marselus Merung; Denny Saleh
Jurnal Health Sains Vol. 7 No. 8 (2026): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v7i8.2870

Abstract

Breast cancer remains a major cause of cancer-related morbidity and mortality among women, and locally advanced disease continues to pose significant therapeutic challenges. Neoadjuvant chemotherapy is commonly administered to reduce tumor burden and improve surgical operability, with anthracycline- and taxane-based regimens being widely used. This study aimed to compare the effectiveness and adverse effects of anthracycline-based and taxane-based neoadjuvant chemotherapy in patients with locally advanced breast cancer at Prof. Dr. R. D. Kandou General Hospital. An observational analytic study with a prospective cohort design was conducted involving 27 female patients, comprising 11 patients who received anthracycline-based chemotherapy and 16 patients who received taxane-based chemotherapy. Tumor response was assessed using Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, while adverse events were evaluated according to the Common Terminology Criteria for Adverse Events (CTCAE). The results showed that partial response was the predominant outcome in both groups, occurring in 81.82% of patients in the anthracycline group and 75% of patients in the taxane group. The Mann–Whitney test revealed no significant difference in treatment effectiveness between the two regimens (p = 0.708). Most adverse effects were mild to moderate, although toxicity patterns differed between the groups. In conclusion, both regimens demonstrated comparable effectiveness, while treatment selection should consider patient characteristics, organ function, tolerability, and regimen-specific adverse-effect risks. These findings support individualized regimen selection based on therapeutic efficacy and anticipated toxicity profiles.
Effectiveness of Artificial Intelligence–Assisted Colonoscopy for Adenoma Detection: A Systematic Review and Meta-Analysis Mutiara Delia Subiyanto; Laura Subiyanto
Jurnal Health Sains Vol. 7 No. 8 (2026): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v7i8.2871

Abstract

Colorectal cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide. Colonoscopy plays a central role in colorectal cancer screening, and the adenoma detection rate (ADR) is a key quality indicator associated with reduced colorectal cancer risk. Recently, artificial intelligence (AI)-based computer-aided detection (CADe) systems have been developed to assist endoscopists in identifying colorectal lesions during colonoscopy. This research aimed to evaluate the effectiveness of artificial intelligence–assisted colonoscopy in improving adenoma detection compared with conventional colonoscopy. A systematic review and meta-analysis were conducted following PRISMA guidelines. Literature searches were performed in PubMed, the Cochrane Library, and ScienceDirect to identify comparative studies evaluating CADe-assisted colonoscopy versus conventional colonoscopy. The primary outcome was adenoma detection rate. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Four studies comprising 10,483 colonoscopy procedures were included in the meta-analysis. The pooled results demonstrated that AI-assisted colonoscopy significantly increased adenoma detection compared with conventional colonoscopy (RR = 1.19; 95% CI = 1.07–1.32; p = 0.002). Moderate heterogeneity was observed among the included studies (I² = 68%). Notably, although overall ADR improved substantially, several studies reported limited or no significant improvement in the detection of advanced colorectal neoplasia, suggesting that the benefit may have been predominantly driven by increased detection of diminutive adenomas. Artificial intelligence–assisted colonoscopy using CADe systems significantly improved adenoma detection rates compared with conventional colonoscopy. However, further large-scale randomized studies are needed to determine whether these improvements translate into clinically meaningful long-term reductions in colorectal cancer incidence and mortality.
Development of an Orthanc Pacs-Based Radiology Information System (RIS) at The Ilyas Tarakan Type D Navy Hospital Nofa Rosalina; Bambang Satoto; Rasyid Rasyid; Alfisna Fajru Rohmah
Jurnal Health Sains Vol. 7 No. 8 (2026): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v7i8.2872

Abstract

Digital transformation in radiology management is urgently needed to improve accuracy, efficiency, and compliance with medical data retention standards. However, many type C and D hospitals in Indonesia still rely on paper- and film-based workflows because commercial Picture Archiving and Communication System (PACS) solutions are costly. This research aimed to design, develop, and evaluate an integrated Radiology Information System (RIS) based on the open-source Orthanc PACS at Ilyas Tarakan Naval Hospital, a type D hospital, to address radiology data fragmentation, limited Digital Imaging and Communications in Medicine (DICOM) storage on modality consoles, and paper-based reporting workflows. A Research and Development (R&D) approach was employed using the Rapid Application Development (RAD) model, consisting of a preliminary study, system development, expert validation through black-box testing, and limited pilot testing using a pre-test/post-test design involving ten respondents. The RIS was developed using Laravel and Bootstrap and integrated with Orthanc PACS through a Modality Worklist (MWL) mechanism. System performance was analyzed using normality, homogeneity, and Mann–Whitney statistical tests. Expert validation showed 100% validity across functionality, performance, user interface, security, compatibility, error handling, and usability aspects, while the integration aspect could not be evaluated due to hospital policy constraints. Pilot testing demonstrated a significant improvement in usability across all seven measured dimensions, with a Mann–Whitney test result of p = 0.000 (p < 0.05). The Orthanc-based RIS-PACS provided an effective and low-cost model for digitizing radiology services in budget-constrained type D hospitals and is recommended for gradual integration with the hospital information system.

Page 79 of 79 | Total Record : 783

 75   76   77   78   79 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 7 No. 8 (2026): Journal Health Sains Vol. 7 No. 7 (2026): Journal Health Sains Vol. 7 No. 5 (2026): Journal Health Sains Vol. 7 No. 4 (2026): Journal Health Sains Vol. 7 No. 3 (2026): Journal Health Sains Vol. 7 No. 2 (2026): Journal Health Sains Vol. 7 No. 1 (2026): Journal Health Sains Vol. 6 No. 12 (2025): Journal Health Sains Vol. 6 No. 11 (2025): Journal Health Sains Vol. 6 No. 10 (2025): Journal Health Sains Vol. 7 No. 6 (2025): Journal Health Sains Vol. 6 No. 9 (2025): Journal Health Sains Vol. 6 No. 8 (2025): Journal Health Sains Vol. 6 No. 7 (2025): Journal Health Sains Vol. 6 No. 6 (2025): Journal Health Sains Vol. 6 No. 5 (2025): Journal Health Sains Vol. 6 No. 4 (2025): Journal Health Sains Vol. 6 No. 3 (2025): Journal Health Sains Vol. 6 No. 2 (2025): Journal Health Sains Vol. 6 No. 1 (2025): Jurnal Health Sains Vol. 5 No. 12 (2024): Jurnal Health Sains Vol. 5 No. 11 (2024): Jurnal Health Sains Vol. 5 No. 10 (2024): Jurnal Health Sains Vol. 5 No. 9 (2024): Journal Health Sains Vol. 5 No. 8 (2024): Journal Health Sains Vol. 5 No. 7 (2024): Journal Health Sains Vol. 5 No. 6 (2024): Journal Health Sains Vol. 5 No. 5 (2024): Journal Health Sains Vol. 5 No. 4 (2024): Journal Health Sains Vol. 5 No. 3 (2024): Journal Health Sains Vol. 5 No. 2 (2024): Jurnal Health Sains Vol. 5 No. 1 (2024): Jurnal Health Sains Vol. 4 No. 12 (2023): Journal Health Sains Vol. 4 No. 11 (2023): Journal Health Sains Vol. 4 No. 10 (2023): Journal Health Sains Vol. 4 No. 9 (2023): Journal Health Sains Vol. 4 No. 8 (2023): Journal Health Sains Vol. 4 No. 7 (2023): Journal Health Sains Vol. 4 No. 6 (2023): Journal Health Sains Vol. 4 No. 5 (2023): Journal Health Sains Vol. 4 No. 4 (2023): Journal Health Sains Vol. 4 No. 3 (2023): Journal Health Sains Vol. 4 No. 2 (2023): Journal Health Sains Vol. 4 No. 1 (2023): Jurnal Health Sains Vol. 3 No. 12 (2022): Jurnal Health Sains Vol. 3 No. 11 (2022): Jurnal Health Sains Vol. 3 No. 10 (2022): Jurnal Health Sains Vol. 3 No. 9 (2022): Jurnal Health Sains Vol. 3 No. 8 (2022): Jurnal Health Sains Vol. 3 No. 7 (2022): Jurnal Health Sains Vol. 3 No. 6 (2022): Jurnal Health Sains Vol. 3 No. 5 (2022): Jurnal Health Sains Vol. 3 No. 4 (2022): Jurnal Health Sains Vol. 3 No. 3 (2022): Jurnal Health Sains Vol. 3 No. 2 (2022): Jurnal Health Sains Vol. 3 No. 1 (2022): Jurnal Health Sains Vol. 2 No. 12 (2021): Jurnal Health Sains Vol. 2 No. 11 (2021): Jurnal Health Sains Vol. 2 No. 10 (2021): Jurnal Health Sains Vol. 2 No. 9 (2021): Jurnal Health Sains Vol. 2 No. 8 (2021): Jurnal Health Sains Vol. 2 No. 7 (2021): Jurnal Health Sains Vol. 2 No. 6 (2021): Jurnal Health Sains Vol. 2 No. 5 (2021): Jurnal Health Sains Vol. 2 No. 4 (2021): Jurnal Health Sains Vol. 2 No. 3 (2021): Jurnal Health Sains Vol. 2 No. 2 (2021): Jurnal Health Sains Vol. 2 No. 1 (2021): Jurnal Health Sains Vol. 1 No. 6 (2020): Jurnal Health Sains Vol. 1 No. 5 (2020): Jurnal Health Sains Vol. 1 No. 4 (2020): Jurnal Health Sains Vol. 1 No. 3 (2020): jurnal health sains Vol. 1 No. 2 (2020): Jurnal Health Sains Vol. 1 No. 1 (2020): Jurnal Health Sains More Issue