Teknologi Informasi Bidang Kedokteran

Abramov, A. V, & Макушкин, Е. В. (2024). Neurodevelopmental Disorders Caused by Genetic Defects in Structure of Glutamatergic Receptors. Psikhiatriya, 22(1), 90–98. https://doi.org/10.30629/2618-6667-2024-22-1-90-98

Adirim T. 2025. . Cham (CH): Springer Nature

Albuquerque, B. H. D. R. de, & Lanza, D. C. F. (2025). Optimizing Gene Prioritization for Clinical Diagnosis of Metabolic Genetic Disorders. Plos One, 20(8), e0331038. https://doi.org/10.1371/journal.pone.0331038

Almarwani, M. S. (2024). The Role of Integrated Health Informatics in Streamlining Patient Flow From Emergency Department to Admission: A Review of Administrative and Clinical Synergies. Saudi Journal of Medicine and Public Health, 1(2), 1927–1934. https://doi.org/10.64483/202412551

Alum, E. U., Ikpozu, E. N., Offor, C. E., Igwenyi, I. O., Obaroh, I. O., Ibiam, U. A., & Ukaidi, C. U. A. (2025). RNA-based Diagnostic Innovations: A New Frontier in Diabetes Diagnosis and Management. Diabetes and Vascular Disease Research, 22(2). https://doi.org/10.1177/14791641251334726

Aneesh, K., Govindaraj, M., & Sam, S. (2022). Design Approaches of Ultra-Low Power SAR ADC for Biomedical Systems — A Review. Journal of Circuits Systems and Computers, 31(12). https://doi.org/10.1142/s0218126622300094

Applegate, C., Schiettecatte, F., Hamosh, A., & Amberger, J. (2022). Exploring Genes and Phenotypes Within Chromosomal Regions Using OMIM’s GeneScout. Current Protocols, 2(9). https://doi.org/10.1002/cpz1.530

Ariani, Y., & Rachmadi, R. A. (2022). Profil Aberasi Kromosom Pasien Malformasi Kongenital Multipel Non-Sindromik. Ejournal Kedokteran Indonesia, 10(2), 114–120. https://doi.org/10.23886/ejki.10.179.114-20

Badreddine, J., Tay, K., Lin, H.-T., Rhodes, S., Schumacher, F. R., Bodner, D. R., & Wu, C. W. (2023). Beyond the Kidney: Extra-Renal Manifestations of Monogenic Nephrolithiasis and Their Significance. https://doi.org/10.1101/2023.05.16.23289588

Birgmeier, J., Haeussler, M., Deisseroth, C. A., Steinberg, E., Jagadeesh, K. A., Ratner, A., Guturu, H., Wenger, A. M., Diekhans, M., Stenson, P. D., Cooper, D. N., Ré, C., Beggs, A. H., Bernstein, J. A., & Bejerano, G. (2020). AMELIE Speeds Mendelian Diagnosis by Matching Patient Phenotype and Genotype to Primary Literature. Science Translational Medicine, 12(544). https://doi.org/10.1126/scitranslmed.aau9113

Biswas, I. (2025). Relational Accountability in AI-driven Pharmaceutical Practices: An Ethics Approach to Bias, Inequity and Structural Harm. Journal of Medical Ethics, jme-2025-110913. https://doi.org/10.1136/jme-2025-110913

Brahimi, S., & Elhussein, M. (2023). Measuring the Effect of Fraud on Data-Quality Dimensions. Data, 8(8), 124. https://doi.org/10.3390/data8080124

Cacheiro, P., Lawson, S., Veyver, I. B. Van den, Marengo, G., Zocche, D., Murray, S. A., Duyzend, M., Robinson, P. N., & Smedley, D. (2024). Lethal Phenotypes in Mendelian Disorders. https://doi.org/10.1101/2024.01.12.24301168

Cai, Z., Zafferani, M., & Hargrove, A. E. (2021). Ensemble Learning-Based Quantitative Structure-Activity Relationship Platform Predicts Binding Behavior of RNA-targeted Small Molecules. https://doi.org/10.26434/chemrxiv-2021-czl9p

Calavia, H. L., Awadalla, M., Nasir, S. A., & Hammel, J. (2022). An Atypical Presentation of Twiddler’s Syndrome: A Case Report. Cureus. https://doi.org/10.7759/cureus.27207

Chaari L. 2019. Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine. Cham (CH): Springer Nature

Chan, M. F., Young, C. F., Gelblum, D., Shi, C., Rincón, C. M., Hipp, E., Li, J., & Wang, D. (2021). A Review and Analysis of Managing Commonly Seen Implanted Devices for Patients Undergoing Radiation Therapy. Advances in Radiation Oncology, 6(4), 100732. https://doi.org/10.1016/j.adro.2021.100732

Chen, S. (2025). Reframing EHR Policy in China: Towards Balanced Implementation and Ethical Foundations. Journal of Evaluation in Clinical Practice, 31(7). https://doi.org/10.1111/jep.70273

Chiu, F. P., Doolan, B. J., McGrath, J. A., & Onoufriadis, A. (2021). A Decade of Next‐generation Sequencing in Genodermatoses: The Impact on Gene Discovery and Clinical Diagnostics*. British Journal of Dermatology, 184(4), 606–616. https://doi.org/10.1111/bjd.19384

Colin, E., Duffourd, Y., Chevarin, M., Tisserant, É., Verdez, S., Paccaud, J., Bruel, A., Mau‐Them, F. T., Denommé‐Pichon, A., Thévenon, J., Safraou, H., Besnard, T., Goldenberg, A., Cogné, B., Isidor, B., Delanne, J., Sorlin, A., Moutton, S., Fradin, M., … Vitobello, A. (2023). Stepwise Use of Genomics and Transcriptomics Technologies Increases Diagnostic Yield in Mendelian Disorders. Frontiers in Cell and Developmental Biology, 11. https://doi.org/10.3389/fcell.2023.1021920

Concu, R., Cordeiro, M. N. D. S., Pérez‐Pérez, M., & Fdez‐Riverola, F. (2023). MOZART, a QSAR Multi-Target Web-Based Tool to Predict Multiple Drug–Enzyme Interactions. Molecules, 28(3), 1182. https://doi.org/10.3390/molecules28031182

Corsten‐Janssen, N., Bouman, K., Diphoorn, J. C. D., Scheper, A. J., Kinds, R., Mecky, J. e., Breet, H., Verheij, J., Suijkerbuijk, R. F., Duin, L., Manten, G. T. R., Langen, I. M. v., Sijmons, R. H., Sikkema‐Raddatz, B., Westers, H., & Diemen, C. C. v. (2020). A Prospective Study on Rapid Exome Sequencing as a Diagnostic Test for Multiple Congenital Anomalies on Fetal Ultrasound. Prenatal Diagnosis, 40(10), 1300–1309. https://doi.org/10.1002/pd.5781

Debauche, O., Penka, J. B. N., Mahmoudi, S., Lessage, X., Hani, M., Manneback, P., Lufuluabu, U. K., Bert, N., Messaoudi, D., & Guttadauria, A. (2022). RAMi: A New Real-Time Internet of Medical Things Architecture for Elderly Patient Monitoring. Information, 13(9), 423. https://doi.org/10.3390/info13090423

Dentico, A., Ferrieri, A., Epicoco, G., Troccoli, R., Carretta, F., D’Agostino, C., & Carretta, D. (2022). P382 follow–up of Patients Submitted to Transvenous Lead Extraction for Endocarditis or Septic Shock and Then Re–implanted With Leadless Pacemaker: Single Center’s Experience. European Heart Journal Supplements, 24(Supplement_C). https://doi.org/10.1093/eurheartj/suac012.368

Faida, E. W., Supriyanto, S., Haksama, S., Markam, H., & Ali, A. (2022). The Acceptance and Use of Electronic Medical Records in Developing Countries Within the Unified Theory of Acceptance and Use of Technology Framework. Open Access Macedonian Journal of Medical Sciences, 10(E), 326–336. https://doi.org/10.3889/oamjms.2022.8409

Fan, C., Chen, M., Wang, X., Wang, J., & Huang, B. (2021). A Review on Data Preprocessing Techniques Toward Efficient and Reliable Knowledge Discovery From Building Operational Data. Frontiers in Energy Research, 9. https://doi.org/10.3389/fenrg.2021.652801

Faria, A. C. d., Daré, J. K., Cunha, E. F. F. da, & Freitas, M. P. (2022). Computer-Assisted Improvement of Sulfonylureas With Antifungal Properties and Limited Herbicidal Activity: Potential Application in Forage Conservation. Journal of Agricultural and Food Chemistry, 70(10), 3321–3330. https://doi.org/10.1021/acs.jafc.1c07352

Fong, B., Fong, A. C. M., & Li, C. K. (2020). Telemedicine Technologies Information Technologies in Medicine and Digital Health (2nd ed.). John Wiley and Sons Ltd.

Gamba, A., Salmona, M., & Bazzoni, G. (2021). The Similarity of Inherited Diseases (I): Clinical Similarity Within the Phenotypic Series. BMC Medical Genomics, 14(1). https://doi.org/10.1186/s12920-021-00900-7

Gaonkar, A., Rath, S., S, R., Jain, M., Swathy Vaman, R., Das, A., Manal, S., Singh Lamba, D., Kaur, P., YADAV, S., Dave, S., Ashok Tawde, A., Misra, S., BM, S., Goyal, C., Bharti, S., & Chaitanya Amerneni, K. (2025). Transforming medical diagnosis: a comprehensive review of AI and ML technologies. Evidence Public Health, 1(1). https://doi.org/10.61505/evipubh.2025.1.1.10

Gaudêncio, S. P., & Pereira, F. (2020). A Computer-Aided Drug Design Approach to Predict Marine Drug-Like Leads for SARS-CoV-2 Main Protease Inhibition. Marine Drugs, 18(12), 633. https://doi.org/10.3390/md18120633

Gaudêncio, S. P., & Pereira, F. (2022). Predicting Antifouling Activity and Acetylcholinesterase Inhibition of Marine-Derived Compounds Using a Computer-Aided Drug Design Approach. Marine Drugs, 20(2), 129. https://doi.org/10.3390/md20020129

Gill, J. (2022). Implantable Cardiovascular Devices: Current and Emerging Technologies for Remote Heart Failure Monitoring. Cardiology in Review, 31(3), 128–138. https://doi.org/10.1097/crd.0000000000000432

Godfrey A, Stuart S. 2021. Digital Health Exploring Use and Integration of Wearables. Chennai (IN): Elsevier

Goel, H., Yu, W., & MacKerell, A. D. (2022). hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties. https://doi.org/10.20944/preprints202205.0255.v1

Görükmez, Ö., Görükmez, O., & Topak, A. (2023). Clinical Exome Sequencing Findings in 1589 Patients. American Journal of Medical Genetics Part A, 191(6), 1557–1564. https://doi.org/10.1002/ajmg.a.63190

Grishin, S. M., & Odintsov, S. V. (2023). Main trends in development and law regulation of electronic health in the European Union. CARDIOMETRY, 25, 25–30. https://doi.org/10.18137/cardiometry.2022.25.2530

Guglietta, E., Denekamp, S., Sinclair, S., Harris, L., Bishop, P. D., Naidoo, N., Holliday, T., Chacko, M., Downey, R., Swanapillai, J., Martin, A., & Webber, M. (2024). Heart Rhythm New Zealand Consensus Statement on the Practical Management of Cardiac Implanted Electronic Devices in the Peri-Operative Environment. NZMJ, 137(1590), 77–92. https://doi.org/10.26635/6965.6363

Gumber, V., Salibi, G., & Tzenios, N. (2025). Modern Approaches to the Management of Patients With Diabetic Nephropathy. Special Journal of the Medical Academy and Other Life Sciences, 3(5). https://doi.org/10.58676/sjmas.v3i5.124

Halim, S. A., Jabeen, S., Khan, A., & Al‐Harrasi, A. (2021). Rational Design of Novel Inhibitors of Α-Glucosidase: An Application of Quantitative Structure Activity Relationship and Structure-Based Virtual Screening. Pharmaceuticals, 14(5), 482. https://doi.org/10.3390/ph14050482

Hamosh, A., Amberger, J., Bocchini, C., Scott, A. F., & Rasmussen, S. A. (2021). Online Mendelian Inheritance in Man (OMIM®): Victor McKusick’s Magnum Opus. American Journal of Medical Genetics Part A, 185(11), 3259–3265. https://doi.org/10.1002/ajmg.a.62407

Hamzeh‐Mivehroud, M., Khoshravan-Azar, Z., & Dastmalchi, S. (2020). QSAR and Molecular Docking Studies on Non-Imidazole-Based Histamine H3 Receptor Antagonists. Pharmaceutical Sciences, 26(2), 165–174. https://doi.org/10.34172/ps.2019.64

Hassan, E. M., & Omenogor, C. E. (2025). AI Powered Predictive Healthcare: Deep learning for Early Diagnosis, Personalized Treatment, and Disease Prevention. International Journal of Science and Research Archive, 14(3), 806–823. https://doi.org/10.30574/ijsra.2025.14.3.0731

Hidayat, A. D. (2022). Integrasi Data Pada Dashboard Sistem Kesehatan (DaSK) Untuk Mendukung Analisa &Amp; Visualisasi Sistem Rujukan. Journal of Information Systems for Public Health, 7(1), 25. https://doi.org/10.22146/jisph.71333

Hidayat, N. A., Sebayang, A. N. O., Shofia, A., & Aldharma, S. A. (2022). Development of Telemedicine Application Based on Artificial Intelligence in the Handling of Diabet Foot. Jurnal Layanan Masyarakat (Journal of Public Services), 6(1), 205–211. https://doi.org/10.20473/jlm.v6i1.2022.205-211

Indriyajati, F., Jawa, M. M. S. D., & Utomo, H. (2023). Analisis Keamanan Data Electronic Medical Record Digital Transformation Office (DTO) Kementerian Kesehatan Indonesia. Sanskara Manajemen Dan Bisnis, 2(01), 59–66. https://doi.org/10.58812/smb.v2i01.130

Jeevarathinam, S., Balasubramanian, P., & Babu, A. B. K. A. (2025). Deep Neuro-Fuzzy Systems for Diabetes Prediction Using Siddha Healthcare Practices With Algorithm Comparison. Indian Journal of Science and Technology, 18(33), 2656–2668. https://doi.org/10.17485/ijst/v18i33.259

Kanan, T., Kanan, D., Shardoub, E. J. A., & Durdağı, S. (2021). Transcription Factor NF-κB as Target for SARS-CoV-2 Drug Discovery Efforts Using Inflammation-Based QSAR Screening Model. Journal of Molecular Graphics and Modelling, 108, 107968. https://doi.org/10.1016/j.jmgm.2021.107968

Karalük, S. (2026). Evaluation of Electrode Impedance, Sensing, and Pacing Threshold Changes at 12 Hours After Pacemaker Implantation. Kocaeli Üniversitesi Sağlık Bilimleri Dergisi, 12(1), 21–26. https://doi.org/10.30934/kusbed.1690782

Khelfa, N., Belaıdı, S., Zerroug, E., Soualmia, F., & Chtita, S. (2023). In Silico-Based Identification of New Anti-PFDHFR Drug Candidates via 1,3,5-Triazine Derivatives. Main Group Chemistry, 22(4), 521–539. https://doi.org/10.3233/mgc-220111

Koçak, H., & Çetin, G. (2023). The Diagnosis of Diabetes Mellitus With Boosting Methods. El-Cezeri Fen Ve Mühendislik Dergisi. https://doi.org/10.31202/ecjse.1242207

Kristanto, B. K., Listio, S. W. P., & Palandi, J. F. (2024). Perancangan Integrasi Sistem Informasi Rumah Sakit Kristen Mojowarno Modul Instalasi Gawat Darurat Dengan Satu Sehat Kementerian Kesehatan Indonesia Menggunakan Metode Scrum. Jurnal Nasional Komputasi Dan Teknologi Informasi (Jnkti), 7(6). https://doi.org/10.32672/jnkti.v7i6.8429

Kuang, R., Pirakalathanan, J., Lau, T., Koh, D., Kotschet, E., Ko, B., & Lau, K. K. (2021). An Up‐to‐date Review of Cardiac Pacemakers and Implantable Cardioverter Defibrillators. Journal of Medical Imaging and Radiation Oncology, 65(7), 896–903. https://doi.org/10.1111/1754-9485.13319

Kunde, P. D., Ramkumar, S., Kamble, S. P., RaviKumar, A., Kulkarni, B. D., & Kumar, V. R. (2021). On the Use of Electronegativity and Electron Affinity Based Pseudo‐molecular Field Descriptors in Developing Correlations for Quantitative Structure‐activity Relationship Modeling of Drug Activities. Chemical Biology & Drug Design, 98(2), 258–269. https://doi.org/10.1111/cbdd.13895

Kurniawan, I., Ambarsari, L., Kurniatin, P. A., & Wahyudi, S. T. (2024). Novel Compounds Design of Acertannin, Hamamelitannin, and Petunidin-3-Glucoside Typical Compounds of African Leaves (Vernonia amygdalina Del) as Antibacterial Based on QSAR and Molecular Docking. Jurnal Jamu Indonesia, 8(2), 29–38. https://doi.org/10.29244/jji.v8i2.326

Kurniawan, I., & Rohmatika, A. U. (2026). Molecular Docking, QSAR, and Bioactivity Prediction of Uncaria gambir Flavonoids as Antibacterial Agents Targeting MurA Enzyme. Biointerface Research in Applied Chemistry, 16(1), 1–22. https://doi.org/https://doi.org/10.33263/BRIAC161.032

Kurniawan, I., & Winarno, N. S. (2025). Unlocking Antibacterial Potential: Thiophene-2-carbaldehyde Modification of Acertannin from African Leaves as MurA Enzyme Inhibitors. Jurnal Ners, 9(4), 7602–7612. https://doi.org/10.31004/jn.v9i4.49392

Lee PC, Wang JTH, Chen TY, Peng CH. 2022. Digital Heal Care in Taiwan Innovations of National Health Insurance. Taiwan: Springer Nature

Lee, J., Han, S. Y., & Kwon, Y. W. (2025). Technological Advances and Medical Applications of Implantable Electronic Devices: From the Heart, Brain, and Skin to Gastrointestinal Organs. Biosensors, 15(8), 543. https://doi.org/10.3390/bios15080543

Lee, K.-S., Chung, Y., & Kim, J. (2024). Research Trends on Metabolic Syndrome in Digital Health Care Using Topic Modeling: Systematic Search of Abstracts. Journal of Medical Internet Research, 26, e53873. https://doi.org/10.2196/53873

Lee, Y., Park, S., Lee, J. S., Kim, S. Y., Cho, J., Yoo, Y., Lee, S., Yoo, T., Lee, M., Seo, J., Lee, J., Kneissl, J., Lee, J., Jeon, H., Jeon, E. Y., Hong, S. E., Kim, E., Kim, H., Kim, W. J., … Chae, J. (2020). Genomic Profiling of 553 Uncharacterized Neurodevelopment Patients Reveals a High Proportion of Recessive Pathogenic Variant Carriers in an Outbred Population. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-58101-8

Li, F., Li, X., Yang, Y., Xu, Y., & Zhang, Y. (2021). Collaborative Production Task Decomposition and Allocation Among Multiple Manufacturing Enterprises in a Big Data Environment. Symmetry, 13(12), 2268. https://doi.org/10.3390/sym13122268

Liu, J., Wang, Q., & Chen, J. (2024). Case Report: A De Novo Variant of CRMP1 in an Individual With a Neurodevelopmental Disorder. Frontiers in Neuroscience, 18. https://doi.org/10.3389/fnins.2024.1490731

Lupski, J. R. (2021). Clan Genomics: From OMIM Phenotypic Traits to Genes and Biology. American Journal of Medical Genetics Part A, 185(11), 3294–3313. https://doi.org/10.1002/ajmg.a.62434

Lusiana, D., & Nilogiri, A. (2023). Model Hot Fit (Human, Organization, Technology Fit) Untuk Evaluasi Penerapan Aplikasi SATUSEHAT. Jsai (Journal Scientific and Applied Informatics), 6(3), 291–302. https://doi.org/10.36085/jsai.v6i3.5795

Mahendra, F. R., Prakoso, I., Marzelino, A., Rizqy Fadhillah, M., Syukriyansyah, Hasibuan, M. M. A., Suparningtyas, J. F., Kristiadi, M., Setiawan, A. G., Rahman, F. I., Sari, A. N., Raysendria, N. R., Kurniawan, I., Arozal, W., & Kusmardi, K. (2025). Optimisation of peptides targeting reverse transcriptase HIV-1 using QSAR, machine learning, and computational approaches. Frontiers in Pharmacology, Volume 16. https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2025.1707377

Matsumoto, K., Miyao, T., & Funatsu, K. (2021). Ranking-Oriented Quantitative Structure–Activity Relationship Modeling Combined With Assay-Wise Data Integration. Acs Omega, 6(18), 11964–11973. https://doi.org/10.1021/acsomega.1c00463

Mehta, V. (2023). Artificial Intelligence in Medicine: Revolutionizing Healthcare for Improved Patient Outcomes. Journal of Medical Research and Innovation, 7(2), e000292. https://doi.org/10.32892/jmri.292

Memon, Q. Z., Iqbal, H., Haider, S., Devi, R., & Maheen, M. (2025). Innovative Approaches in Pediatric Medicine: Emerging Trends and Future Perspectives. Journal of Medical & Health Sciences Review, 2(2). https://doi.org/10.62019/yt7jq302

Moon, Y., Lee, Y., Hwang, Y., & Jeong, J. (2024). Long Short-Term Memory Autoencoder and Extreme Gradient Boosting-Based Factory Energy Management Framework for Power Consumption Forecasting. Energies, 17(15), 3666. https://doi.org/10.3390/en17153666

Muhammad, M. (2025). Diabetes Virtual Assistant “Divistant”: Asisten Digital Berbasis Chatbot Untuk Hidup Lebih Baik Dengan Diabetes. Jurnal Informatika Dan Teknik Elektro Terapan, 13(3S1). https://doi.org/10.23960/jitet.v13i3s1.7712

Mwogosi, A. (2025). Leveraging AI to Enhance Healthcare Delivery in Tanzania: Innovations and Ethical Imperatives. Sage Open, 15(3). https://doi.org/10.1177/21582440251378162

Naurah, G., Simarmata, M., & Jambak, R. S. (2024). Hak Dan Privasi Pasien Rumah Sakit Di Era Digitalisasi. Comserva Jurnal Penelitian Dan Pengabdian Masyarakat, 3(12), 4798–4805. https://doi.org/10.59141/comserva.v3i12.1295

Nazir, A. (2025). Wearable Technology and Its Potential Role in Cardiovascular Health Monitoring and Disease Management. Health Science Reports, 8(11). https://doi.org/10.1002/hsr2.71486

Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2021). BEdgeHealth: A Decentralized Architecture for Edge-Based IoMT Networks Using Blockchain. Ieee Internet of Things Journal, 8(14), 11743–11757. https://doi.org/10.1109/jiot.2021.3058953

Niazi, S. K., & Mariam, Z. (2023). Recent Advances in Machine Learning-Based Chemoinformatics: A Comprehensive Review. https://doi.org/10.20944/preprints202306.0803.v1

Nishikiori, K., Tanaka, K., & Uesawa, Y. (2022). Construction of a Prediction Model for Drug Removal Rate in Hemodialysis Based on Chemical Structures. Molecular Diversity, 26(5), 2647–2657. https://doi.org/10.1007/s11030-021-10348-7

Nyavor, H. (2025). Al Powered Disease, Prevention: Predicting Health Risks Through Machine Learning for Proactive Care Approaches. International Journal of Science and Research Archive, 15(1), 479–495. https://doi.org/10.30574/ijsra.2025.15.1.1018

Olen, M., Dechert, B. E., Foster, A., Kanter, R. J., Silka, M. J., & Shah, M. J. (2021). Variations in Cardiac Implantable Electronic Device Surveillance and Ancillary Testing in the Paediatric and Congenital Heart Disease Population: An International Multi-Centre Survey From the Paediatric and Congenital Electrophysiology Society. Cardiology in the Young, 32(1), 101–105. https://doi.org/10.1017/s104795112100425x

Patil, K. S., & Rufus, E. (2022). Microwave Antennas Suggested for Biomedical Implantation. https://doi.org/10.5772/intechopen.101060

Pividori, M., Rajagopal, P. S., Barbeira, A., Liang, Y., Melia, O., Bastarache, L., Park, Y., Consortium, Gte., Wen, X., & Im, H. K. (2020). PhenomeXcan: Mapping the Genome to the Phenome Through the Transcriptome. Science Advances, 6(37). https://doi.org/10.1126/sciadv.aba2083

Pradita, R., & Fitriana, S. M. (2024). Implementasi Standar Interoperabilitas HL7-FHIR Pada Pertukaran Rekam Kesehatan Elektronik Di Puskesmas. Jurnal Ilmiah Perekam Dan Informasi Kesehatan Imelda (Jipiki), 9(1), 20–30. https://doi.org/10.52943/jipiki.v9i1.1334

Prakash, A. (2024). Pre-Processing Techniques for Preparing Clean and High-Quality Data for Diabetes Prediction. International Journal of Research Publication and Reviews, 5(2), 458–465. https://doi.org/10.55248/gengpi.5.0224.0412

R, J., Aqid, B., Salsabula, A. P., & Nurfiyanti, K. (2025). Implementation of EMR System in Indonesian Health Facilities: Benefits and Constraints. Journal of Indonesian Health Policy and Administration, 10(1). https://doi.org/10.7454/ihpa.v10i1.1140

Rezha, D. K., & Ismah, Z. (2024). Analisis Pengaruh Paparan Asap Rokok Terhadap Kejadian Osteoporosis Pada Wanita Usia 50-59. Media Kesehatan Masyarakat Indonesia, 23(2), 134–140. https://doi.org/10.14710/mkmi.23.2.134-140

Rim, J. H., Choi, Y. J., & Gee, H. Y. (2020). Genomic Landscape and Mutational Spectrum of ADAMTS Family Genes in Mendelian Disorders Based on Gene Evidence Review for Variant Interpretation. Biomolecules, 10(3), 449. https://doi.org/10.3390/biom10030449

Riska, P., Retno, K., & Rhuccy, N. (2024). Upaya Pengelolaan Penyakit Diabetes Mellitus Melalui Interoperabilitas Personal Health Record. Infokes Jurnal Ilmiah Rekam Medis Dan Informatika Kesehatan, 14(1), 50–57. https://doi.org/10.47701/infokes.v14i1.3668

Rosas-Jiménez, J. G., García‐Revilla, M. A., Madariaga‐Mazón, A., & Martínez‐Mayorga, K. (2020). A Validated and Interpretable Predictive Model of Cruzain Inhibitors. https://doi.org/10.1101/2020.06.02.129411

Rubiyanti, N. S. (2023). Penerapan Rekam Medis Elektronik Di Rumah Sakit Di Indonesia: Kajian Yuridis. Aladalah, 1(1), 179–187. https://doi.org/10.59246/aladalah.v1i1.163

Samajdar, S. S., Saboo, B., Joshi, S., Makkar, B., Narwaria, M., Kapoor, N., Deshpande, N., Mehta, R., Mukherjee, S., & Saboo, B. (2025). Unraveling the Dual Burden of Diabetes and Obesity: Precision Strategies for South Asian Populations. International Journal of Diabetes and Technology, 4(3), 55–66. https://doi.org/10.4103/ijdt.ijdt_15_25

Sandhe, D. S. K., Krisnana, I., & Pradanie, R. (2025). Innovations for Successful Electronic Medical Records (EMR) Implementation in Hospitals. Indonesian Journal of Innovation Studies, 26(2). https://doi.org/10.21070/ijins.v26i2.1360

Saporito, D., Celentano, E., Amellone, C., Zanotto, G., Baroni, M., Miracapillo, G., Biffi, M., Calvi, V., Spighi, L., Curnis, A., Pisanò, E., Rovaris, G., Senatore, G., Caravati, F., Notarangelo, F. M., Marini, M., Solimene, F., Piacenti, M., Tomasi, L., … Giammaria, M. (2024). Magnetic Resonance-Conditional Cardiac Implantable Electronic Devices: An Italian Perspective on the Prevalence of Mixed-Brand Systems Over Time. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-73403-x

Savai, S., Hasan, M. K., Kamano, J., Misoi, L., Wakholi, P., & Were, M. C. (2022). Data Cleaning Process for mHealth Log Data to Inform Health Worker Performance. https://doi.org/10.3233/shti220664

Sciarra, L., Salustri, E., Petroni, R., Calò, L., Delise, P., Penco, M., & Romano, S. (2020). Sport Activity in Patients With Cardiac Implantable Electronic Devices: Evidence and Perspectives. Journal of Cardiovascular Medicine, 22(5), 335–343. https://doi.org/10.2459/jcm.0000000000001093

Sharma D, Singh S, Mittal M. 2022. Bioinformatics and RNA A practice Based Approach: Boca Raton (US): CRC Press Taylor and Francis Group

Shayanfar, S., & Shayanfar, A. (2022). Comparison of Various Methods for Validity Evaluation of QSAR Models. BMC Chemistry, 16(1). https://doi.org/10.1186/s13065-022-00856-4

Shuja, N. (2024). The Future of Personalized Medicine. Dev. Med. Life Sci., 1(7), 1–3. https://doi.org/10.69750/dmls.01.07.084

Sobreira, N., Repetto, G. M., Temtamy, S. A., & Pérez, A. B. A. (2021). Using Online Mendelian Inheritance in Man in Low‐ and Middle‐income Countries. American Journal of Medical Genetics Part A, 185(11), 3284–3286. https://doi.org/10.1002/ajmg.a.62467

Songma, S., Sathuphan, T., & Pamutha, T. (2023). Optimizing Intrusion Detection Systems in Three Phases on the CSE-CIC-IDS-2018 Dataset. Computers, 12(12), 245. https://doi.org/10.3390/computers12120245

Strik, M., Ploux, S., Zande, J. v. d., Velraeds, A., Fontagne, L., Haı̈ssaguerre, M., & Bordachar, P. (2024). The Use of Electrocardiogram Smartwatches in Patients With Cardiac Implantable Electrical Devices. Sensors, 24(2), 527. https://doi.org/10.3390/s24020527

Susanti, S., & Maulana, A. (2024). Evaluasi Kinerja Pada Aplikasi SatuSehat Menggunakan Metode Pieces. Ijcit (Indonesian Journal on Computer and Information Technology), 9(1). https://doi.org/10.31294/ijcit.v9i1.17637

Susanto, E., & Sugiharto. (2017). Manajemen Informasi Kesehatan IV: Etika Profesi dan Hukum Kesehatan (Edisi Tahu). Kementerian Kesehatan Republik Indonesia.

Takeda, K., Takeuchi, K., Sakuratani, Y., & Kimbara, K. (2024). Improvement of Biodegradability Prediction QSAR System Through Optimal Combination of Algorithms. Iop Conference Series Materials Science and Engineering, 1318(1), 12003. https://doi.org/10.1088/1757-899x/1318/1/012003

Tobb, K., Corbisiero, R., Fish, F. A., Kazemian, P., & Muller, D. (2020). An Alarming Change: What Caused an Instance of Inappropriate Detection in a Wearable Cardioverter-Defibrillator? Journal of Innovations in Cardiac Rhythm Management, 11(2), 3986–3988. https://doi.org/10.19102/icrm.2020.110201

Tonegawa‐Kuji, R., Inoue, Y., Nakai, M., Kanaoka, K., Sumita, Y., Miyazaki, Y., Wakamiya, A., Shimamoto, K., Ueda, N., Nakajima, K., Wada, M., Kamakura, T., Yamagata, K., Ishibashi, K., Miyamoto, K., Nagase, S., Aiba, T., Miyamoto, Y., Iwanaga, Y., & Kusano, K. (2023). Differences in Patient Characteristics, Clinical Practice and Outcomes of Cardiac Implantable Electric Device Therapy Between Japan and the USA: A Cross-Sectional Study Using Data From Nationally Representative Administrative Databases. BMJ Open, 13(1), e068124. https://doi.org/10.1136/bmjopen-2022-068124

Upendra, B., Panigrahi, B. K., Singh, K., & Sabareesh, G. R. (2023). Recent Advancements in Piezoelectric Energy Harvesting for Implantable Medical Devices. Journal of Intelligent Material Systems and Structures, 35(2), 129–155. https://doi.org/10.1177/1045389x231200144

Uzan, G. S., Yaramış, A. H., Sönmezler, E., Kurul, S. H., Yaramis, A., Yiş, U., Günay, Ç., Lochmüller, H., Horváth, R., Oktay, Y., & Yaramış, A. (2025). Pontocerebellar Hypoplasia and Periventricular Leukomalacia Associated With p.Phe262Val Homozygous Variant in TTC1 Gene: A Report of 4 Cases. International Journal of Developmental Neuroscience, 85(5). https://doi.org/10.1002/jdn.70031

Valdespino-Saldaña, E. (2026). Artificial Intelligence-Driven Transformation of Pediatric Diabetes Care: A Systematic Review and Epistemic Meta-Analysis of Diagnostic, Therapeutic, and Self-Management Applications. International Journal of Molecular Sciences, 27(2), 802. https://doi.org/10.3390/ijms27020802

Veletić, M., Apu, E. H., Simić, M., Bergsland, J., Balasingham, I., Contag, C. H., & Ashammakhi, N. (2022). Implants With Sensing Capabilities. Chemical Reviews, 122(21), 16329–16363. https://doi.org/10.1021/acs.chemrev.2c00005

Wan, E. Y., Rogers, A. J., Lavelle, M. P., Marcus, M., Stone, S., Ottoboni, L., Srivatsa, U. N., Leal, M. A., Russo, A. M., Jackson, L. R., & Crossley, G. H. (2024). Periprocedural Management and Multidisciplinary Care Pathways for Patients With Cardiac Implantable Electronic Devices: A Scientific Statement From the American Heart Association. Circulation, 150(8). https://doi.org/10.1161/cir.0000000000001264

Wang, B., He, Y., Wen, X., & Xi, Z. (2022). Prediction and Molecular Field View of Drug Resistance in HIV-1 Protease Mutants. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-07012-x

Wassan, S., Latif, R. M. A., Liudajun, Han, Y., Farhan, M., & Akbar, W. (2025). Advancements in Optical Glucose Sensing for Diabetes Diagnostics and Monitoring. Microwave and Optical Technology Letters, 67(4). https://doi.org/10.1002/mop.70190

Xü, Z., Jin, C., Cabe, A., Escobedo, D., Hao, N., Trase, I., Closson, A. B., Dong, L., Nie, Y., Elliott, J., Feldman, M. D., Chen, Z., & Zhang, J. X. J. (2020). Flexible Energy Harvester on a Pacemaker Lead Using Multibeam Piezoelectric Composite Thin Films. Acs Applied Materials & Interfaces, 12(30), 34170–34179. https://doi.org/10.1021/acsami.0c07969

Yadav, M., Narasimhan, B., & Kapoor, A. (2024). Development of 2-Dimensional and 3-Dimensional QSAR Models of Indazole Derivatives as TTK Inhibitors Having Anticancer Potential. Current Chemistry Letters, 13(1), 225–240. https://doi.org/10.5267/j.ccl.2023.6.006

Yavuz, S., Elnazir, B., Amin, S., Sherif, A., Saif, S., & Francis, N. (2024). A Unique Mutation in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Gene Causing Cystic Fibrosis in a Pakistani Child: A Case Highlighting the Need for More Awareness. Cureus. https://doi.org/10.7759/cureus.54627

Yu, T.-H., Su, B., Battalora, L. C., Liu, S., & Tseng, Y. J. (2021). Ensemble Modeling With Machine Learning and Deep learning to Provide Interpretable Generalized Rules for Classifying CNS Drugs With High Prediction Power. Briefings in Bioinformatics, 23(1). https://doi.org/10.1093/bib/bbab377

Zhang, J., & Zhang, Z. (2023). Ethics and Governance of Trustworthy Medical Artificial Intelligence. BMC Medical Informatics and Decision Making, 23(1). https://doi.org/10.1186/s12911-023-02103-9

Zhang W. 2016. Computer Aided Drug Discovery. New York (US): Humana Press Springer Nature

Zhu, Q., Nguyễn, Ð.-T., Sid, E., & Pariser, A. (2020). Leveraging the UMLS as a Data Standard for Rare Disease Data Normalization and Harmonization. Methods of Information in Medicine, 59(04/05), 131–139. https://doi.org/10.1055/s-0040-1718940