Challenges of Applying AI in Healthcare in India

被引:3
作者
Nizam, Verda [1 ]
Aslekar, Avinash [1 ]
机构
[1] Symbiosis Int Deemed Univ, Symbiosis Inst Digital & Telecom Management, Pune, Maharashtra, India
关键词
AI; challenges; healthcare; India; physicians; rural communities; ARTIFICIAL-INTELLIGENCE;
D O I
10.9734/JPRI/2021/v33i36B31969
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
With the advent of digitalization, upcoming technologies like Artificial Intelligence (AI) are being utilized by healthcare services to manage various healthcare services to mimic human cognitive functions. This technology is expected to bring about a massive change in healthcare. Patient management, clinical decision support, patient tracking, and health care services are the four main AI-enabled fields of the healthcare industry. The method carrying out the study was based on secondary research by the themes of the studies performed earlier using Artificial intelligence in healthcare sector, through observations, interviews and valid documentations from prominent databases, by means of challenges and its analysis and the last by the issues associated with the study and the target groups are the front line workers in healthcare sectors. The AI applications in health care have gathered much attention, but AI's adoption issues have not been significantly tended. There are several challenges of its implementation, such as resolving the unequal relationship between trained physicians and patients and increasing physicians' efficiency to be more effective in their work; providing AI-enabled healthcare equipment in rural communities; and educating physicians or doctors in handling it. AI technologies have the potential to enhance patient outcomes. Still, they may also pose significant risks in terms of inadequate patient risk assessment, medical error, and suggestions for treatment, privacy violations, and others.
引用
收藏
页码:203 / 209
页数:7
相关论文
共 16 条
[1]  
Academy of Medical Royal Colleges, 2019, ARTIF INTELL
[2]   A fuzzy interpretive structural modeling approach for evaluating the factors affecting lean implementation in Indian healthcare industry [J].
Ajmera, Puneeta ;
Jain, Vineet .
INTERNATIONAL JOURNAL OF LEAN SIX SIGMA, 2019, 11 (02) :376-397
[3]  
[Anonymous], 2019, ARTIFICIAL INTELLIGENCE IN GLOBAL HEALTH Defining a Collective Path Forward
[4]  
Bali J, 2020, INDIA 4 IND REVOLUTI
[5]   Artificial intelligence enabled healthcare: A hype, hope or harm [J].
Bhattacharya, Sudip ;
Pradhan, Keerti Bhusan ;
Abu Bashar, Md ;
Tripathi, Shailesh ;
Semwal, Jayanti ;
Marzo, Roy Rillera ;
Bhattacharya, Sandip ;
Singh, Amarjeet .
JOURNAL OF FAMILY MEDICINE AND PRIMARY CARE, 2019, 8 (11) :3461-3464
[6]   A Failure to “Do No Harm” -- India’s Aadhaar biometric ID program and its inability to protect privacy in relation to measures in Europe and the U.S. [J].
Dixon P. .
Health and Technology, 2017, 7 (4) :539-567
[7]  
Gujral G., 2020, P NAT C HIVR SHSS TI
[8]   The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries [J].
Guo, Jonathan ;
Li, Bin .
HEALTH EQUITY, 2018, 2 (01) :174-181
[9]  
Haider H., 2020, Barriers to the Adoption of Artificial Intelligence in Healthcare in India
[10]   Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry [J].
Kamble, Sachin S. ;
Gunasekaran, Angappa ;
Sharma, Rohit .
COMPUTERS IN INDUSTRY, 2018, 101 :107-119