Purohit Saraswati1,* Suneel kumar2
1Assistant Professor HOD, Department of Psychiatric Nursing, JSS College of Nursing, Mysuru, India
2Assistant Lecturer JSS College of Nursing, Mysuru, India
*Corresponding author: Mrs Purohit Saraswati, Assistant Professor, HOD Department of Psychiatric Nursing, JSS College of Nursing, Mysuru, India, Email: [email protected]
Received Date: June 15, 2024
Published Date: September 20, 2024
Citation: Saraswati P, et al. (2024). AI in Health Care: A Comprehensive Review. Mathews J Nurs. 6(4):52.
Copyrights: Saraswati P, et al. © (2024).
INTRODUCTION
Artificial Intelligence is transforming the healthcare industry by providing innovative solutions to elevate patient care, enhance results, and lower expenses. This analysis delves into the existing uses, advantages, obstacles, and upcoming advancements of AI in healthcare.
APPLICATIONS OF AI IN HEALTH CARE
Diagnosis and Detection
Predictive Analytics
Machine learning algorithms forecast patient outcomes by analyzing past data, aiding in the early identification of high-risk individuals and the prevention of negative incidents.
Disease Outbreaks: AI has the capability to examine patterns derived from diverse data sources in order to anticipate and monitor the occurrence of disease outbreaks, thereby facilitating prompt interventions.
Personalized Medicine
CLINICAL DECISION SUPPORT
ROBOTICS AND AUTOMATION
REMOTE MONITORING AND TELEHEALTH
BENEFITS OF AI IN HEALTH CARE
Enhanced Precision: AI enhances diagnostic precision and treatment effectiveness through the analysis of extensive data sets with great accuracy.
Improved Productivity: Implementing automation for administrative and clinical tasks enhances the efficiency of healthcare providers by reducing their workload and optimizing operational processes.
AI plays a crucial role in cutting down healthcare expenses through enhancing productivity, expediting the process of drug discovery, and reducing the likelihood of hospital readmissions.
AI plays a crucial role in cutting down healthcare expenses through enhancing productivity, expediting the process of drug discovery, and reducing the likelihood of hospital readmissions.
CHALLENGES AND ETHICAL CONSIDERATIONS
Safeguarding the privacy and security of health data is of utmost importance. AI systems need to adhere to regulations like HIPAA and GDPR to ensure compliance.
Addressing biases in AI models that stem from training data is essential to prevent disparities in healthcare. Promoting fairness and equity in AI applications is critical.
Enhancing the transparency of AI models, especially deep learning algorithms, is crucial as they can often be opaque. This is vital for building trust among clinicians and ensuring patient safety.
Navigating the regulatory approval and legal challenges surrounding the use of AI in healthcare can be intricate and time-consuming.
FUTURE DIRECTIONS
Advancements in AI Technology: Continuous improvements in AI algorithms, especially in areas like explainable AI and reinforcement learning, will enhance their applicability in healthcare.
Integration with Clinical Practice: Developing robust frameworks for the integration of AI into clinical practice will ensure that AI supports but does not replace human clinicians.
Research and Validation: Extensive clinical trials and validation studies are necessary to establish the efficacy and safety of AI applications in healthcare.
Interdisciplinary Collaboration: Collaboration between AI researchers, clinicians, ethicists, and policymakers will drive the responsible development and deployment of AI in healthcare.
CONCLUSION
AI has the potential to revolutionize the field of healthcare through its ability to enhance diagnostic accuracy, personalize treatments, and improve overall efficiency. It is crucial to address the challenges and ethical concerns that come with integrating AI into healthcare systems in order to ensure its successful implementation. Through ongoing advancements and interdisciplinary collaboration, AI is set to play a crucial role in shaping the future of healthcare.
REFERENCES