scholarly journals Legal Urgency on Designing The Legislation for The Use of Artificial Intelligence in Indonesian Medical Practice

2021 ◽  
Vol 21 (4) ◽  
pp. 541
Author(s):  
Hary Abdul Hakim ◽  
Chrisna Bagus Edhita Praja ◽  
Hardianto Djanggih
Keyword(s):  
Artificial Intelligence ◽  
Medical Practice ◽  
Healthcare Costs ◽  
Descriptive Analysis ◽  
High Accuracy ◽  
Health Law ◽  
Disease Treatment ◽  
Medical Practices ◽  
Medical Diagnoses ◽  
Legal Documents

Artificial intelligence (AI) offers the potential for a great improvement in patient care, both in diagnose and disease treatment, and a consequential reduction in healthcare costs, a part of opportunities and challenge are ahead. The use of AI in medicine was significantly developed in some countries. Indonesia as a modern country also has a great change in promoting the use of AI. The study aims to propose on designing the legislation for the use of AI in Indonesian medical practices. The method used in this research is normative juridical approaches with descriptive analysis. The data used are primary legal material namely the Indonesian Penal Code and Law No. 36 of 2009 on Health Law. Meanwhile, the secondary legal material used are books, journals, and other legal documents. The results show that designing the new legislation as the guidance and basis for the use of AI shall give a good impact on the development of health services as practices among other countries. Moreover, Health Act 2009 clearly supported the use of advance technology’s product in medicine. Yet, the application of AI facilitates interpretation follows with high accuracy and speed for medical diagnoses.

scholarly journals A Descriptive Study of Thailand’s ESP Programs: Policy Implications for AEC

2015 ◽  
Vol 6 (3) ◽  
pp. 30-36
Author(s):  
Kantatip Sinhaneti
Keyword(s):  
Medical Practice ◽  
Descriptive Analysis ◽  
Descriptive Study ◽  
Policy Implications ◽  
The Other ◽  
International Programs ◽  
Public And Private ◽  
Medical Practices ◽  
Land Surveying ◽  
Master Level

As a country member, Thailand needs to prepare for the upcoming AEC. One way to look at how the country has prepared for this is to look at the ESP programs offered in universities, both public and private, especially ESP programs in preparation for the eight careers: engineering, hospitality & tourism, architecture, dentistry, medical practices, accounting, surveying, nursing. This study therefore explores the AEC careers offered in public and private universities. This was a descriptive study. The international programs under study fell into two levels: Bachelor (335 programs) and Master (436 programs). The results of descriptive analysis revealed these findings. On the eight AEC careers, three most popular programs offered in Thailand included hospitality & tourism, engineering and accounting respectively. On the other hand, no land surveying programs are offered at both levels; no dentistry programs at Bachelor level; no medical practice is offered at Master level. For policy implication, Thailand should offer these programs in the future.

The Globalization of Health Law: The Case of Permissibility of Placebo-based Research

2000 ◽  
Vol 26 (2-3) ◽  
pp. 175-186
Author(s):  
Timothy S. Jost
Keyword(s):  
Health Care ◽  
Medical Practice ◽  
Health Care Professionals ◽  
Global Markets ◽  
Health Law ◽  
Cross Border ◽  
Internet Pharmacies ◽  
The Individual ◽  
Global Communications ◽  
National Borders

If any trend can be confidently predicted for the next millennium (or, more modestly, for our lifetimes) it is the globalization of health law. We live in an age of global markets and global communications. While care of the individual patient has remained largely local, national borders are quite porous to health care professionals. The cross-border flow of patients is a significant factor in some regions, and the development of telemedicine and internet pharmacies is radically expanding the possibility of cross-border medical practice.

scholarly journals Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

2020 ◽  
Vol 6 ◽  
pp. 205520762096835
Author(s):  
C Blease ◽  
C Locher ◽  
M Leon-Carlyle ◽  
M Doraiswamy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Medical Profession ◽  
Descriptive Analysis ◽  
Psychiatric Practice ◽  
Limited Attention ◽  
Written Responses ◽  
Future Technology ◽  
Qualitative Descriptive ◽  
The Impact

Background The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. Objective This study aimed to explore psychiatrists’ opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice Methods In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses (“comments”) to three open-ended questions in the survey. Results Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that ‘man and machine’ would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention. Conclusions This study presents timely information on psychiatrists’ views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

The intervention of artificial intelligence in the recruitment function in UAE’s hospitality industry

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Bharti Pandya ◽  
Maryam Mohammed Al Janahi
Keyword(s):  
Artificial Intelligence ◽  
Thematic Analysis ◽  
Hospitality Industry ◽  
Descriptive Analysis ◽  
Recruitment Strategies ◽  
Human Intervention ◽  
Job Descriptions ◽  
Job Advertisements ◽  
Routine Tasks ◽  
Hospitality Sector

Artificial Intelligence (AI) is not a new concept for Hospitality Industry and Recruitment functions. AI has displaced the human intervention in routine tasks. In few years, AI will take over several jobs (Kubler, 2018). Recently AI technologies support application screening, data analysis, and preliminary interviews, saving time of recruiters. Chatbots are now designated recruitment officers supporting candidates. Researchers have studied the influence of AI on Recruitment, but only a few focused on the AI displacing human in the recruitment function performed in UAE’s hospitality industry. This research aims to understand the transformation in the recruitment function of UAE’s hospitality industry due to AI intervention. Using concurrent mixed-methods, data was collected by interviewing 10 UAE HR leaders and surveying 135 HR professionals. The inductive-deductive thematic analysis was conducted for subjective measures and descriptive analysis was performed for scaled measures. This study found that UAE’s hospitality sector deployed AI technologies in recruitment areas such as job advertisements, collecting applications, maintaining profiles, and storing the applications. The routine, repetitive, and heavy-volume tasks in the recruitment are delegated to AI while strategic roles are retained for human professionals including development of strategies, and creation of job descriptions and specifications. While the literature review suggested a wider application of AI in recruitment function, UAE’s hospitality sector seems to be lagging. The recommendations will benefit industry leaders, HR professionals, recruitment consultants, and AI developers to rethink on the recruitment strategies, operations, and administration and to embrace the intervention of AI in recruiting the best talent proficiently.

scholarly journals Application of Artificial Intelligence Techniques in Predicting the Lost Circulation Zones Using Drilling Sensors

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Abdulmalek Ahmed ◽  
Salaheldin Elkatatny ◽  
Abdulwahab Ali ◽  
Mahmoud Abughaban ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Drilling Fluid ◽  
Confusion Matrix ◽  
High Accuracy ◽  
Functional Networks ◽  
Lost Circulation ◽  
Drilling Parameters ◽  
High Pressure High Temperature ◽  
Drilling Cost

Drilling a high-pressure, high-temperature (HPHT) well involves many difficulties and challenges. One of the greatest difficulties is the loss of circulation. Almost 40% of the drilling cost is attributed to the drilling fluid, so the loss of the fluid considerably increases the total drilling cost. There are several approaches to avoid loss of return; one of these approaches is preventing the occurrence of the losses by identifying the lost circulation zones. Most of these approaches are difficult to apply due to some constraints in the field. The purpose of this work is to apply three artificial intelligence (AI) techniques, namely, functional networks (FN), artificial neural networks (ANN), and fuzzy logic (FL), to identify the lost circulation zones. Real-time surface drilling parameters of three wells were obtained using real-time drilling sensors. Well A was utilized for training and testing the three developed AI models, whereas Well B and Well C were utilized to validate them. High accuracy was achieved by the three AI models based on the root mean square error (RMSE), confusion matrix, and correlation coefficient (R). All the AI models identified the lost circulation zones in Well A with high accuracy where the R is more than 0.98 and RMSE is less than 0.09. ANN is the most accurate model with R=0.99 and RMSE=0.05. An ANN was able to predict the lost circulation zones in the unseen Well B and Well C with R=0.946 and RMSE=0.165 and R=0.952 and RMSE=0.155, respectively.

scholarly journals Artificial Intelligence Analysis of Gene Expression Predicted the Overall Survival of Mantle Cell Lymphoma and a Large Pan-Cancer Series

Healthcare ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 155
Author(s):  
Joaquim Carreras ◽  
Naoya Nakamura ◽  
Rifat Hamoudi
Keyword(s):  
Artificial Intelligence ◽  
Overall Survival ◽  
B Cell ◽  
Mantle Cell Lymphoma ◽  
Cell Lymphoma ◽  
High Accuracy ◽  
Gene Set Enrichment Analysis ◽  
Intelligence Analysis ◽  
Mantle Cell ◽  
Pan Cancer

Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and conventional statistics, correlated 20,862 genes with 28 MCL prognostic genes for dimensionality reduction, to predict the patients’ overall survival and highlight new markers. As a result, 58 genes predicted survival with high accuracy (area under the curve = 0.9). Further reduction identified 10 genes: KIF18A, YBX3, PEMT, GCNA, and POGLUT3 that associated with a poor survival; and SELENOP, AMOTL2, IGFBP7, KCTD12, and ADGRG2 with a favorable survival. Correlation with the proliferation index (Ki67) was also made. Interestingly, these genes, which were related to cell cycle, apoptosis, and metabolism, also predicted the survival of diffuse large B-cell lymphoma (GSE10846, n = 414), and a pan-cancer series of The Cancer Genome Atlas (TCGA, n = 7289), which included the most relevant cancers (lung, breast, colorectal, prostate, stomach, liver, etcetera). Secondly, survival was predicted using 10 oncology panels (transcriptome, cancer progression and pathways, metabolic pathways, immuno-oncology, and host response), and TYMS was highlighted. Finally, using machine learning, C5 tree and Bayesian network had the highest accuracy for prediction and correlation with the LLMPP MCL35 proliferation assay and RGS1 was made. In conclusion, artificial intelligence analysis predicted the overall survival of MCL with high accuracy, and highlighted genes that predicted the survival of a large pan-cancer series.

scholarly journals Analisis Hukum Perjanjian Penyembuhan Kepada Pasien Dari Penyelenggara Praktik Pengobatan Tradisional

PRANATA HUKUM ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. 133-142
Author(s):  
Rissa Afni Martinouva
Keyword(s):  
Traditional Medicine ◽  
Health Care Providers ◽  
Traditional Healers ◽  
Health Law ◽  
Care Providers ◽  
Legal Certainty ◽  
Community Members ◽  
Traditional Treatment ◽  
Medical Practices ◽  
Treatment Providers

The organization of traditional medicine practices is an alternative healing path besides medical methods. The practice of traditional medicine must be supported by a health law device intended to provide legal certainty and protection for community members as patients and traditional treatment providers. This study is intended to find out the regulations that protect the organization of traditional medical practices and the forms of healing agreements provided by providers of traditional medical practices for patients. The research method used is normative by reviewing regulations, literature studies and observations of traditional medicine. The implementation of traditional medical practices is supported by several regulations including the Minister of Health Decree No. 1076 / MENKES / SK / VII / 2003 concerning Traditional Medicine Administrators and Law No. 36 of 2009 concerning Health. The health law instrument is intended to provide legal certainty and protection for community members as patients and traditional treatment providers. The traditional treatment agreement is clear that if carried out in accordance with the procedures specified by law is a legal agreement and binds the parties to traditional healers and patients. The type of agreement used by traditional healers and patients is a healing agreement (therapeutic agreement). A therapeutic agreement is a term of agreement that deals with a doctor that also applies to traditional healing staff as health care providers. Healing agreements within the scope of traditional medicine are not currently supported by clarifying the legal requirements of the agreement specifically.

scholarly journals The Greek origin of caduceum: Æsculapius.

1969 ◽  
Vol 39 (4) ◽  
pp. 384-393
Author(s):  
Arturo G. Rillo
Keyword(s):  
Medical Practice ◽  
Human Life ◽  
Spiritual Life ◽  
Medical Practices ◽  
Real Environment ◽  
Medicine History

Introduction: Medicine history gives us the chance to reflect about the Caduceus as the synthesis of the dialectic of the sensible and spiritual life. This opens and horizon of comprehension and allow us to recover the legend of Asclepius and it’s cult with the different symbolic elements that structure it. The legend: The historic and mythological references about Asclepius’ existence gives structure to the legend in a real and not-real environment perduring in the occidental medicine tradition as a mystical reference to the deity for the medical practice. The cult: It’s based in the incubation and synthesizes healing rites and therapeutical practices, as medical as surgical; exercise, sleep cures and amusement activities. The symbol: The linguistic origin of Asclepius’ name, the symbolism of the legend protagonists and the iconographic representation of their attributes, converge in the Caduceus to represent the medical practices and ideas synthesis, all them related to the human life. Conclusion: Asclepius’ perception transcends the Olympic divinity and situates him as the healing archetype; that’s why Caduceus is consistent with the system-world representation that rules the actual medical practice.

scholarly journals TINJAUAN PENANGANAN KASUS MALPRAKTEK MEDIS DI PENGADILAN PIDANA DALAM PERSPEKTIF HUKUM KESEHATAN

2019 ◽  
Vol 35 (1) ◽  
Author(s):  
Albertus Soge
Keyword(s):  
Health Services ◽  
Medical Practice ◽  
Medical Malpractice ◽  
Legal Protection ◽  
Criminal Court ◽  
Health Law ◽  
Long Period ◽  
Legal Uncertainty ◽  
The Law

Legislation on Health Law is a Lex Specialist law that contains exceptional norms for legal protection for providers and receivers of health services. Law Number 36 of 2009 on Health and Law Number 29 of 2004 on Medical Practice are not used consistently in resolving medical malpractice cases in the Criminal Court, thus causing injustice and legal uncertainty. Incorrect application of the law and a long period of cases resolution in court requires reform in handling medical malpractice cases.

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