AI In Medical Applications
- Research Writing
- Literature Review
- What is a Literature Review?
- What are the different (Three) Phases of Literature Review?
- What are the different steps and strategies followed while writing a Literature review?
- Moves in the Literature review (Structure) – Schematic Structure
- What are the different Standards for doctoral literature reviews (Boote and Beile, 2005)
- How to Read, Summarize, and critique previous studies (Seliger and Shohamy, 1989)
- A Checklist to ensure as to whether a piece of writing is academic or not
- Important factors to consider when evaluating a reference for an academic article / dissertation
- How to organize your literature review and the critics from examiners for your literature review
AI In Medical Applications
Artificial Intelligence (AI) is a branch of computer science concerned with the creation of intelligent machines capable of performing tasks similar to those performed by humans. This human-created intelligence began more than 60 years ago. The goal of previous generations of applications was to demonstrate generic human-like behaviour. The incredible development made over time cannot be dismissed, as systems become more sophisticated and capable of achieving their many goals. The goal goes beyond the basics with the advancement and increased compliance of this technology. It includes industries such as health care, video games, and smart devices. Artificial Intelligence in Medicine (AIM) is the use of complicated algorithms and programmes in the diagnosis and treatment of patients, as well as the comparative study of complex medical data, all without the involvement of a human.
Medical Data Mining and Artificial Intelligence
Hospitals are currently adopting the Electronic Health Record (EHR) system all over the world,[26], and the same format is used in many healthcare facilities in India. The main benefit of this method is that it allows for quick and precise data capture and storage. Medical records can be converted to digital format using AI ideas such as Optical Character Recognition, Natural Language Processing, and speech recognition algorithms. [27].
Artificial intelligence in other disciplines
AI applications in anaesthesiology have been proposed and tested, including monitoring anaesthetic depth and control, risk prediction, ultrasound guidance, and operating room logistics. [32] In psychiatry, AI approaches are being refined and improved in order to more objectively diagnose mental illnesses and to discover illnesses at an earlier stage, when interventions are more likely to be helpful. [33] Several research in ophthalmology have used image processing algorithms to identify diabetic retinopathy (DR). [34]
Future of Artificial Intelligence in Healthcare
Validating AI tools to increase competence and utility is a major issue for the future. A mutually beneficial collaboration between AI and health care experts is required. AI will assist medical practitioners in becoming more efficient or cost-effective AI tools where clinicians may supply the data and clinical experience needed to construct smarter models. [42] Several technologies in dermatology, radiology, and laboratory medicine have been shown to be more accurate than professionals in the fields. The Ministry of Health and Family Welfare in India has released a national digital health plan that includes AI and machine learning deployment guidelines. [43] However, technological adoption in the public health sector cannot be compared to that in the banking, tourist, and transportation industries, which are all profit-driven. [44] It will be fascinating to watch to what extent and when AI-enabled technologies will replace the intimate knowledge of humans. [1].