Displaying publications 1 - 20 of 61 in total

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  1. Salleh MIM, Abdullah R, Zakaria N
    BMC Med Inform Decis Mak, 2021 02 25;21(1):75.
    PMID: 33632216 DOI: 10.1186/s12911-021-01447-4
    BACKGROUND: The Ministry of Health of Malaysia has invested significant resources to implement an electronic health record (EHR) system to ensure the full automation of hospitals for coordinated care delivery. Thus, evaluating whether the system has been effectively utilized is necessary, particularly regarding how it predicts the post-implementation primary care providers' performance impact.

    METHODS: Convenience sampling was employed for data collection in three government hospitals for 7 months. A standardized effectiveness survey for EHR systems was administered to primary health care providers (specialists, medical officers, and nurses) as they participated in medical education programs. Empirical data were assessed by employing partial least squares-structural equation modeling for hypothesis testing.

    RESULTS: The results demonstrated that knowledge quality had the highest score for predicting performance and had a large effect size, whereas system compatibility was the most substantial system quality component. The findings indicated that EHR systems supported the clinical tasks and workflows of care providers, which increased system quality, whereas the increased quality of knowledge improved user performance.

    CONCLUSION: Given these findings, knowledge quality and effective use should be incorporated into evaluating EHR system effectiveness in health institutions. Data mining features can be integrated into current systems for efficiently and systematically generating health populations and disease trend analysis, improving clinical knowledge of care providers, and increasing their productivity. The validated survey instrument can be further tested with empirical surveys in other public and private hospitals with different interoperable EHR systems.

    Matched MeSH terms: Electronic Health Records*
  2. Sayyah Gilani M, Iranmanesh M, Nikbin D, Zailani S
    Inform Health Soc Care, 2017 Mar;42(2):153-165.
    PMID: 27100821 DOI: 10.3109/17538157.2016.1160245
    Electronic medical records (EMRs) have been proven to be effective tools for improving the safety and quality of healthcare despite their relatively low usage rate in hospitals. The long-term development by EMRs depends on the continued use of healthcare professionals. In this study, technology continuance theory (TCT) was used to evaluate the short-term and long-term continuance acceptance of EMRs among healthcare professionals. Data were gathered by surveying 195 medical professionals in Iran. The data were analyzed using the partial least squares (PLS) technique. The analysis showed that the TCT provided a deep understanding of user continuance intention toward EMRs. In addition, the findings illustrated that the determinants of continuance intention vary between short-term and long-term users. The theoretical and practical implications of the study are discussed.
    Matched MeSH terms: Electronic Health Records/utilization*
  3. Hussien HM, Yasin SM, Udzir SNI, Zaidan AA, Zaidan BB
    J Med Syst, 2019 Sep 14;43(10):320.
    PMID: 31522262 DOI: 10.1007/s10916-019-1445-8
    Blockchain in healthcare applications requires robust security and privacy mechanism for high-level authentication, interoperability and medical records sharing to comply with the strict legal requirements of the Health Insurance Portability and Accountability Act of 1996. Blockchain technology in the healthcare industry has received considerable research attention in recent years. This study conducts a review to substantially analyse and map the research landscape of current technologies, mainly the use of blockchain in healthcare applications, into a coherent taxonomy. The present study systematically searches all relevant research articles on blockchain in healthcare applications in three accessible databases, namely, ScienceDirect, IEEE and Web of Science, by using the defined keywords 'blockchain', 'healthcare' and 'electronic health records' and their variations. The final set of collected articles related to the use of blockchain in healthcare application is divided into three categories. The first category includes articles (i.e. 43/58 scientific articles) that attempted to develop and design healthcare applications integrating blockchain, particularly those on new architecture, system designs, framework, scheme, model, platform, approach, protocol and algorithm. The second category includes studies (i.e., 6/58 scientific articles) that attempted to evaluate and analyse the adoption of blockchain in the healthcare system. Finally, the third category comprises review and survey articles (i.e., 6/58 scientific articles) related to the integration of blockchain into healthcare applications. The final articles for review are discussed on the basis of five aspects: (1) year of publication, (2) nationality of authors, (3) publishing house or journal, (4) purpose of using blockchain in health applications and the corresponding contributions and (5) problem types and proposed solutions. Additionally, this study provides identified motivations, open challenges and recommendations on the use of blockchain in healthcare applications. The current research contributes to the literature by providing a detailed review of feasible alternatives and identifying the research gaps. Accordingly, researchers and developers are provided with appealing opportunities to further develop decentralised healthcare applications through a comprehensive discussion of about the importance of blockchain and its integration into various healthcare applications.
    Matched MeSH terms: Electronic Health Records/standards
  4. Kiah ML, Haiqi A, Zaidan BB, Zaidan AA
    Comput Methods Programs Biomed, 2014 Nov;117(2):360-82.
    PMID: 25070757 DOI: 10.1016/j.cmpb.2014.07.002
    The use of open source software in health informatics is increasingly advocated by authors in the literature. Although there is no clear evidence of the superiority of the current open source applications in the healthcare field, the number of available open source applications online is growing and they are gaining greater prominence. This repertoire of open source options is of a great value for any future-planner interested in adopting an electronic medical/health record system, whether selecting an existent application or building a new one. The following questions arise. How do the available open source options compare to each other with respect to functionality, usability and security? Can an implementer of an open source application find sufficient support both as a user and as a developer, and to what extent? Does the available literature provide adequate answers to such questions? This review attempts to shed some light on these aspects.
    Matched MeSH terms: Electronic Health Records/organization & administration*
  5. Kiah ML, Nabi MS, Zaidan BB, Zaidan AA
    J Med Syst, 2013 Oct;37(5):9971.
    PMID: 24037086 DOI: 10.1007/s10916-013-9971-2
    This study aims to provide security solutions for implementing electronic medical records (EMRs). E-Health organizations could utilize the proposed method and implement recommended solutions in medical/health systems. Majority of the required security features of EMRs were noted. The methods used were tested against each of these security features. In implementing the system, the combination that satisfied all of the security features of EMRs was selected. Secure implementation and management of EMRs facilitate the safeguarding of the confidentiality, integrity, and availability of e-health organization systems. Health practitioners, patients, and visitors can use the information system facilities safely and with confidence anytime and anywhere. After critically reviewing security and data transmission methods, a new hybrid method was proposed to be implemented on EMR systems. This method will enhance the robustness, security, and integration of EMR systems. The hybrid of simple object access protocol/extensible markup language (XML) with advanced encryption standard and secure hash algorithm version 1 has achieved the security requirements of an EMR system with the capability of integrating with other systems through the design of XML messages.
    Matched MeSH terms: Electronic Health Records*
  6. Yusof MM
    Int J Med Inform, 2015 Jul;84(7):486-99.
    PMID: 25881560 DOI: 10.1016/j.ijmedinf.2015.03.001
    Clinical information systems have long been used in intensive care units but reports on their adoption and benefits are limited. This study evaluated a Critical Care Information System implementation.
    Matched MeSH terms: Electronic Health Records/utilization*
  7. Yang Y, Østbye T, Tan SB, Abdul Salam ZH, Ong BC, Yang KS
    J Diabetes Complications, 2011 Nov-Dec;25(6):382-6.
    PMID: 21983153 DOI: 10.1016/j.jdiacomp.2011.08.002
    BACKGROUND:
    Among other risk factors, renal disease and ethnicity have been associated with diabetic lower extremity amputation (LEA) in Western populations. However, little is known about risk factors for LEA among Asian patients.

    OBJECTIVE:
    The objective was to assess the proportion of hospitalized patients with diabetes who have a LEA among all hospital patients with diabetes mellitus (DM) and to investigate risk factors for diabetic LEA (especially renal disease and ethnicity) using hospital discharge database.

    METHOD:
    A retrospective study of hospital discharge database (2004-2009) was performed to identify patients with DM, LEA and renal disease using the International Statistical Classification of Diseases and Related Health Problems, Ninth Revision, Australian Modification codes.

    RESULTS:
    Of 44 917 hospitalized patients with DM during the 6 years, 7312 (16.3%) patients had renal disease, and 1457 (3.2%) patients had LEA. DM patients with renal disease had significant higher rates of LEA (7.1%) compared to DM patients without renal disease (2.5%, P < .001). The differences were present for foot (2.7% vs. 1.2%), ankle or leg (2.8% vs. 0.9%), and knee or above amputation (1.6% vs. 0.4%, all P
    Matched MeSH terms: Electronic Health Records
  8. Tham TY, Tran TL, Prueksaritanond S, Isidro JS, Setia S, Welluppillai V
    Clin Interv Aging, 2018;13:2527-2538.
    PMID: 30587945 DOI: 10.2147/CIA.S185048
    A rapidly aging population along with the increasing burden of patients with chronic conditions in Asia requires efficient health systems with integrated care. Although some efforts to integrate primary care and hospital care in Asia are underway, overall care delivery remains fragmented and diverse, eg, in terms of medical electronic record sharing and availability, patient registries, and empowerment of primary health care providers to handle chronic illnesses. The primary care sector requires more robust and effective initiatives targeted at specific diseases, particularly chronic conditions such as diabetes, hypertension, depression, and dementia. This can be achieved through integrated care - a health care model of collaborative care provision. For successful implementation of integrated care policy, key stakeholders need a thorough understanding of the high-risk patient population and relevant resources to tackle the imminent population demographic shift due to the extremely rapid rate of increase in the aging population in Asia.
    Matched MeSH terms: Electronic Health Records
  9. Tsai TF
    Br J Dermatol, 2023 Sep 15;189(4):361-362.
    PMID: 37379585 DOI: 10.1093/bjd/ljad197
    Matched MeSH terms: Electronic Health Records
  10. Ghaibeh AA, Kasem A, Ng XJ, Nair HLK, Hirose J, Thiruchelvam V
    Stud Health Technol Inform, 2018;247:386-390.
    PMID: 29677988
    The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.
    Matched MeSH terms: Electronic Health Records
  11. Goh CC, Koh KH, Goh S, Koh Y, Tan NC
    Malays Fam Physician, 2018;13(2):10-18.
    PMID: 30302178
    Introduction: Achieving optimal glycated hemoglobin (HbA1c), blood pressure (BP), and LDL-Cholesterol (LDL-C) in patients mitigates macro- and micro-vascular complications, which is the key treatment goal in managing type 2 diabetes mellitus (T2DM). This study aimed to determine the proportion of patients in an urban community with T2DM and the above modifiable conditions attaining triple vascular treatment goals based on current practice guidelines.

    Methods: A questionnaire was distributed to adult Asian patients with dyslipidemia at two primary care clinics (polyclinics) in northeastern Singapore. The demographic and clinical data for this sub-population with both T2DM and dyslipidemia were collated with laboratory and treatment information retrieved from their electronic health records. The combined data was then analyzed to determine the proportion of patients who attained triple treatment goals, and logistic regression analysis was used to identify factors associated with this outcome.

    Results: 665 eligible patients [60.5% female, 30.5% Chinese, 35% Malays, and 34.4% Indians] with a mean age of 60.6 years were recruited. Of these patients, 71% achieved LDL-C ≤2.6 mmol/L, 70.4% had BP

    Matched MeSH terms: Electronic Health Records
  12. Wong PL, Sii HL, P'ng CK, Ee SS, Yong Oong X, Ng KT, et al.
    Influenza Other Respir Viruses, 2020 05;14(3):286-293.
    PMID: 32022411 DOI: 10.1111/irv.12691
    BACKGROUND: Age is an established risk factor for poor outcomes in individuals with influenza-related illness, and data on its influence on clinical presentations and outcomes in the South-East Asian settings are scarce. The aim of this study was to determine the above among adults with influenza-related upper respiratory tract infection at a teaching hospital in Malaysia.

    METHODS: A retrospective case-note analysis was conducted on a cohort of 3935 patients attending primary care at the University Malaya Medical Centre, Malaysia from February 2012 till May 2014 with URTI symptoms. Demographics, clinical characteristics, medical and vaccination history were obtained from electronic medical records, and mortality data from the National Registration Department. Comparisons were made between those aged <25, ≥25 to <65 and ≥65 years.

    RESULTS: 470 (11.9%) had PCR-confirmed influenza virus infection. Six (1.3%) received prior influenza vaccination. Those aged ≥65 years were more likely to have ≥2 comorbidities (P health outcomes. Our findings will now inform future health policies on older persons and economic modelling of adult vaccination programmes.

    Matched MeSH terms: Electronic Health Records
  13. Haddad A, Habaebi MH, Elsheikh EAA, Islam MR, Zabidi SA, Suliman FEM
    PLoS One, 2024;19(4):e0301371.
    PMID: 38557695 DOI: 10.1371/journal.pone.0301371
    To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments.
    Matched MeSH terms: Electronic Health Records
  14. Tay KH, Ariffin F, Sim BL, Chin SY, Sobry AC
    Malays J Med Sci, 2019 Jul;26(4):101-109.
    PMID: 31496899 MyJurnal DOI: 10.21315/mjms2019.26.4.12
    Background: Antimicrobial resistance is a global problem that is perpetuated by the inappropriate use of antibiotics among doctors. This study aims to assess the antibiotic prescription rate for patients with acute upper respiratory infection (URI) and acute diarrhoea.

    Methods: A completed clinical audit cycle was conducted in 2018 in the busy emergency department of a public hospital in Malaysia. Pre- and post-intervention antibiotic prescription data were collected, and changes were implemented through a multifaceted intervention similar to Thailand's Antibiotics Smart Use programme.

    Results: Data from a total of 1,334 pre-intervention and 1,196 post-intervention patients were collected from the hospital's electronic medical records. The mean (SD) age of participants was 19.88 (17.994) years. The pre-intervention antibiotic prescription rate was 11.2% for acute diarrhoea and 29.1% for acute URI, both of which are above the average national rates. These antibiotic prescription rates significantly reduced post-intervention to 6.2% and 13.7%, respectively, falling below national averages. Antibiotic prescription rate was highest for young children. There were no significant changes in rates of re-attendance or hospital admission following the intervention.

    Conclusion: The multifaceted intervention, which included continuing medical education, physician reminders and patient awareness, was effective in improving the antibiotic prescription rates for these two conditions.

    Matched MeSH terms: Electronic Health Records
  15. Zamli AH, Mustafah NM, Sa'at N, Shaharom S
    Med J Malaysia, 2020 11;75(6):642-648.
    PMID: 33219171
    INTRODUCTION: Neurogenic bladder (NB) is a recognized secondary medical impairment following spinal cord injury (SCI). Ultrasound (US) of the kidneys, ureters and bladder (KUB) has been recommended as a useful, non-invasive surveillance method with good diagnostic sensitivity. This study aims to understand US diagnosed NB complications and identify its associated factors.

    METHODS: We enrolled all patients referred for SCI rehabilitation from 2012 to 2015 that fulfilled our study criteria. Data that were retrospectively reviewed included demographic and clinical characteristic data; and US KUB surveillance studies.

    RESULTS: Out of 136 electronic medical records reviewed, 110 fulfilled the study criteria. The prevalence of NB in our study population was 80.9%. We found 22(20%) of the patients showed evidence of US diagnosed NB complications with the mean detection of 9.61±7.91 months following initial SCI. The reported NB complications were specific morphological changes in the bladder wall 8(36.4%); followed by unilateral/bilateral hydronephrosis 7(31.8%); bladder and/or renal calculi 5(22.7%); and mixed complication 2(9.1%) respectively. Half of the patients with NB complications had urodynamic diagnosis of neurogenic detrusor overactivity with/without evidence of detrusor sphincter dyssynergia. We found co-existing neurogenic bowel, presence of spasticity and mode of bladder management were significantly associated factors with US diagnosed NB complications (p<0.05), while spasticity was its predictor with adjusted Odds Ratio value of 3.93 (1.14, 13.56).

    CONCLUSION: NB is a common secondary medical impairment in our SCI population. A proportion of them had US diagnosed NB complications. Co-existing neurogenic bowel, presence of spasticity and mode of bladder management were its associated factors; while spasticity was its predictor.

    Matched MeSH terms: Electronic Health Records
  16. Simon SK, Seldon HL
    Stud Health Technol Inform, 2012;182:125-32.
    PMID: 23138087
    A target of telehealth is to maintain or improve the health of people outside the normal healthcare infrastructure. A modern paradigm in healthcare, and one which fits perfectly with telehealth, is "person self-monitoring", and this fits with the concept of "personal health record" (PHR). One factor in maintaining health is to monitor physiological parameters; this is of course especially important in people with chronic maladies such as diabetes or heart disease. Parameters to be monitored include blood pressure, pulse rate, temperature, weight, blood glucose, oxygen saturation, electrocardiogram (ECG), etc. So one task within telehealth would be to help monitor an individual's physiological parameters outside of healthcare institutions and store the results in a PHR in a way which is available, comprehensible and beneficial to the individual concerned and to healthcare providers. To date many approaches to this problem have been fragmented - emphasizing only part of the problem - or proprietary and not freely verifiable. We describe a framework to approach this task; it emphasizes the implementation of standards for data acquisition, storage and transmission in order to maximize the compatibility among disparate components, e.g. various PHR systems. Data from mobile biosensors is collected on a smartphone using the IEEE 11073 standard where possible; the data can be stored in a PHR on the phone (using standard formats) or can be converted in real-time into more useful information in the PHR, which is based on the International Classification for Primary Care (ICPC2e). The phone PHR data or information can be uploaded to a central online PHR using either the Wi-Fi or GSM transmission protocol together with the Continuity of Care Record message format (CCR, ASTM E2369).
    Matched MeSH terms: Electronic Health Records/instrumentation; Electronic Health Records/organization & administration*
  17. Ali A, Al-Rimy BAS, Tin TT, Altamimi SN, Qasem SN, Saeed F
    Sensors (Basel), 2023 Aug 28;23(17).
    PMID: 37687931 DOI: 10.3390/s23177476
    Precision medicine has emerged as a transformative approach to healthcare, aiming to deliver personalized treatments and therapies tailored to individual patients. However, the realization of precision medicine relies heavily on the availability of comprehensive and diverse medical data. In this context, blockchain-enabled federated learning, coupled with electronic medical records (EMRs), presents a groundbreaking solution to unlock revolutionary insights in precision medicine. This abstract explores the potential of blockchain technology to empower precision medicine by enabling secure and decentralized data sharing and analysis. By leveraging blockchain's immutability, transparency, and cryptographic protocols, federated learning can be conducted on distributed EMR datasets without compromising patient privacy. The integration of blockchain technology ensures data integrity, traceability, and consent management, thereby addressing critical concerns associated with data privacy and security. Through the federated learning paradigm, healthcare institutions and research organizations can collaboratively train machine learning models on locally stored EMR data, without the need for data centralization. The blockchain acts as a decentralized ledger, securely recording the training process and aggregating model updates while preserving data privacy at its source. This approach allows the discovery of patterns, correlations, and novel insights across a wide range of medical conditions and patient populations. By unlocking revolutionary insights through blockchain-enabled federated learning and EMRs, precision medicine can revolutionize healthcare delivery. This paradigm shift has the potential to improve diagnosis accuracy, optimize treatment plans, identify subpopulations for clinical trials, and expedite the development of novel therapies. Furthermore, the transparent and auditable nature of blockchain technology enhances trust among stakeholders, enabling greater collaboration, data sharing, and collective intelligence in the pursuit of advancing precision medicine. In conclusion, this abstract highlights the transformative potential of blockchain-enabled federated learning in empowering precision medicine. By unlocking revolutionary insights from diverse and distributed EMR datasets, this approach paves the way for a future where healthcare is personalized, efficient, and tailored to the unique needs of each patient.
    Matched MeSH terms: Electronic Health Records
  18. Hazim, W., Roszaman, R.
    MyJurnal
    Introduction: In the past, patients with previous abdominal surgery were discouraged from laparoscopic surgery because of perceived increased risk of bowel injury caused by needle and trocar insertion. However, data on the feasibility and safety of surgery of this nature is increasing. We aim to evaluate the surgical outcome of laparoscopic ovarian cystectomy/oophorectomy in previous abdominal surgery. Methods: This is a cross-sectional study with descriptive analysis of retrospective data collection from the electronic medical records of women with laparoscopic ovarian cystectomy/ oophorectomy from January 2000 until Dec 2008. Results from patients with previous abdominal surgery were compared with those of women without prior abdominal surgery. Results: Three hundred and seventeen (317) laparoscopic cystectomies/ oophorectomies were performed during the study period. 71 patients (22.5%) had previous history of abdominal surgery. Adhesions were found in 72% of patients versus 40% (p=0.001) who had previous abdominal surgery but the conversion to open surgery rate was similar (3%, p < 0.05). There was no significant difference in blood loss (134.1 ml ±18.6 vs 119.0 ml ± 9.5), operating time (107 min ± 42.0 versus 102.6 min ± 42.6) and postoperative hospital stay (1.92 days ± 1.0 vs 1.91 days ± 0.7 ). The incidence of peri-operative and post-operative complication showed no significant difference in those who had undergone previous abdominal surgery than those without prior abdominal surgery (p=0.7). The overall complication rate in this series was 0.32 %. Conclusion: Laparoscopic cystectomy/ oophorectomy in the previous abdominal surgery is safe with no increase in morbidity.
    Matched MeSH terms: Electronic Health Records
  19. Ahmadi H, Nilashi M, Ibrahim O, Raisian K
    Curr Health Sci J, 2016 03 29;42(1):82-93.
    PMID: 30568817 DOI: 10.12865/CHSJ.42.01.12
    As Electronic Medical Records (EMRs) have a great possibility for rising physician's performance in their daily work which improves quality, safety and efficiency in healthcare, they are implemented throughout the world (Boonstra and Broekhuis, 2010). In physician practices the rate of EMRs adoption has been slow and restricted (around 25%) according to Endsley, Baker, Kershner, and Curtin (2005) in spite of the cost savings through lower administrative costs and medical errors related with EMRs systems. The core objective of this research is to identify, categorize, and analyse meso-level factors introduced by Lau et al, 2012, perceived by physicians to the adoption of EMRs in order to give more knowledge in primary care setting. Finding was extracted through questionnaire which distributed to 350 physicians in primary cares in Malaysia to assess their perception towards EMRs adoption. The findings showed that Physicians had positive perception towards some features related to technology adoption success and emphasized EMRs had helpful impact in their office. The fuzzy TOPSIS physician EMRs adoption model in meso-level developed and its factors and sub-factors discussed in this study which provide making sense of EMRs adoption. The related factors based on meso-level perspective prioritized and ranked by using the fuzzy TOPSIS. The purpose of ranking using these approaches is to inspect which factors are more imperative in EMRs adoption among primary care physicians. The result of performing fuzzy TOPSIS is as a novelty method to identify the critical factors which assist healthcare organizations to inspire their users in accepting of new technology.
    Matched MeSH terms: Electronic Health Records
  20. Kumar R, Khan FU, Sharma A, Aziz IB, Poddar NK
    Curr Med Chem, 2021 Apr 04.
    PMID: 33820515 DOI: 10.2174/0929867328666210405114938
    There is substantial progress in artificial intelligence (AI) algorithms and their medical sciences applications in the last two decades. AI-assisted programs have already been established for remotely health monitoring using sensors and smartphones. A variety of AI-based prediction models available for the gastrointestinal inflammatory, non-malignant diseases, and bowel bleeding using wireless capsule endoscopy, electronic medical records for hepatitis-associated fibrosis, pancreatic carcinoma using endoscopic ultrasounds. AI-based models may be of immense help for healthcare professionals in the identification, analysis, and decision support using endoscopic images to establish prognosis and risk assessment of patient's treatment using multiple factors. Although enough randomized clinical trials are warranted to establish the efficacy of AI-algorithms assisted and non-AI based treatments before approval of such techniques from medical regulatory authorities. In this article, available AI approaches and AI-based prediction models for detecting gastrointestinal, hepatic, and pancreatic diseases are reviewed. The limitation of AI techniques in such disease prognosis, risk assessment, and decision support are discussed.
    Matched MeSH terms: Electronic Health Records
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