PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 21, 2023Cureus60 citationsOpen Access

Perspective of Artificial Intelligence in Disease Diagnosis: A Review of Current and Future Endeavours in the Medical Field

VUVidhya Rekha UmapathySBSuba Rajinikanth BRRRajkumar Densingh Samuel Raj

Key Points

Key points are not available for this paper at this time.

Abstract

Artificial intelligence (AI) has demonstrated significant promise for the present and future diagnosis of diseases. At the moment, AI-powered diagnostic technologies can help physicians decipher medical pictures like X-rays, magnetic resonance imaging, and computed tomography scans, resulting in quicker and more precise diagnoses. In order to make a prospective diagnosis, AI algorithms may also examine patient information, symptoms, and medical background. The application of AI in disease diagnosis is anticipated to grow as the field develops. In the future, AI may be used to find patterns in enormous volumes of medical data, aiding in disease prediction and prevention before symptoms appear. Additionally, by combining genetic data, lifestyle data, and environmental variables, AI may help in the diagnosis of complicated diseases. It is crucial to remember that while AI can be a powerful tool, it cannot take the place of qualified medical personnel. Instead, AI ought to support and improve diagnostic procedures, enhancing patient care and healthcare results. Future research and the use of AI for disease diagnosis must take ethical issues, data protection, and ongoing model validation into account.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Umapathy et al. (2023) studied this question.

synapsesocial.com/papers/6a0500dbd6c05e8e9519c282https://doi.org/10.7759/cureus.45684
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Delivering healthcare remotely to cardiovascular patients during COVID-192020 · 121 citations
  2. 2Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps2018 · 124 citations
  3. 3Predicting high-cost patients by Machine Learning: A case study in an Australian private hospital group2019 · 11 citations
  4. 4On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work.2019 · 40 citations
  5. 5Personalized Federated Learning With Differential Privacy2020 · 355 citations