AI and Medical Sciences
Enhanced Diagnostics and Treatment
AI algorithms can analyze vast amounts of medical data, including images, patient records, and research findings, to identify patterns and insights that might be missed by human clinicians. This can lead to earlier and more accurate diagnoses, personalized treatment plans, and improved patient outcomes. For instance, AI-powered systems can detect subtle anomalies in medical images, such as X-rays or MRIs, aiding radiologists in identifying diseases like cancer in their early stages. AI can also analyze a patient's genetic information and medical history to predict their risk of developing certain conditions and recommend preventive measures.
Streamlined Healthcare Operations
AI can automate administrative tasks, such as scheduling appointments, managing medical records, and processing insurance claims, freeing up healthcare professionals' time to focus on patient care. AI-powered chatbots can answer patients' basic medical queries, provide appointment reminders, and offer personalized health advice, improving patient engagement and satisfaction. Moreover, AI can optimize hospital operations by predicting patient flow, managing bed availability, and reducing wait times, leading to increased efficiency and cost savings.
Drug Discovery and Development
AI is accelerating the drug discovery process by analyzing vast datasets of molecular information to identify potential drug candidates and predict their efficacy and safety. AI algorithms can also be used to optimize clinical trials, making them more efficient and less costly. This can lead to the development of new treatments for diseases that currently lack effective therapies.
Challenges and Ethical Considerations
Despite its immense potential, AI in healthcare also faces challenges. Ensuring the accuracy and reliability of AI algorithms is crucial, as errors can have serious consequences for patients. Addressing biases in data used to train AI models is also essential to avoid disparities in care. Additionally, ethical considerations surrounding data privacy, security, and the potential displacement of human healthcare professionals need to be carefully addressed.
Topic of AI in Medical Journals
Citing AI
The AMA and CSE both explicitly state that you should not be citing AI in your references. However, if you do use AI you must disclose that in your references.
AMA Template: AI Interface. Version X.X. AI Program; Year. Access Date
AMA Example: ChatGPT. Version 4.0. OpenAI; 2024. Accessed November 1, 2024
If you use AI software to generate content that is included in an assignment, in text you should explain that you have used a particular software tool to do so, and provide a citation for the software.
CSE Template: (AI Program, AI Interface, Access Date)
CSE Example: (OpenAI, ChatGPT, 1 November 2024)
AI and Medical Sciences Books
Artificial Intelligence in Biomedical and Modern Healthcare Informatics
Discusses fundamental and advanced approaches as well as optimization techniques used in AI for healthcare systems
Responsible Use of AI Tools
AI tools offer great potential, but use them cautiously. Sharing data risks exposing sensitive information (e.g., patient/student data, IP), causing privacy, compliance, and security issues. AI-generated information may be inaccurate, so always verify it. Follow these guidelines:
- Only upload open-access articles. Never upload proprietary articles.
- Never enter protected data (PHI, PII, etc.) into AI tools like ChatGPT or Co-Pilot.
- Always fact-check AI information with reliable sources.
- FERPA and HIPAA compliance: Ensure that the use of AI does not compromise the confidentiality of education or health records.
AI in Medical Databases
PubMed uses artificial intellegence to improve the search results and sort them by relevance. PubMed also has AI-powered research assistants that can summarize scientific literature.
PubMed's Best Match sorting algorithm exemplifies how AI affects search results in ways users can't see or aren't aware of.
Artificial intelligence behind the scenes: PubMed's Best Match algorithm
Computed Author uses machine learning to improve PubMed search results by resolving author name ambiguity. It groups articles likely written by the same author, even if others share the same name, improving search effectiveness and supporting NLM's mission.
The National Library of Medicine (NLM) is now using artificial intelligence (AI) to automatically tag medical articles in its MEDLINE database with Medical Subject Headings (MeSH). This automated system, called the Medical Text Indexer (MTI), uses deep learning and other techniques to quickly and accurately index the huge volume of new medical research. This speeds up the process and makes it easier for people to find relevant articles.
Babski D. NLM is a Leader in Using AI to Improve User Experiences. February 2, 2022. Accessed February 6, 2025. https://nlmdirector.nlm.nih.gov/2022/02/02/nlm-is-a-leader-in-using-ai-to-improve-user-experiences/
Information Has Value
The Information Has Value Guide provides details and resources on algorithms, generative AI, digital privacy, and evaluating information online.
Ways to use AI
- Developing research paper topics and keywords.
- Simplifying complex information.
- Summarizing and outlining.