Large Language Models in Ophthalmology : Potential and Pitfalls
Large language models (LLMs) show great promise in assisting clinicians in general, and ophthalmology in particular, through knowledge synthesis, decision support, accelerating research, enhancing education, and improving patient interactions. Specifically, LLMs can rapidly summarize the latest literature to keep clinicians up-to-date. They can also analyze patient data to highlight crucial insights and recommend appropriate tests or referrals. LLMs can automate tedious research tasks like data cleaning and literature reviews. As AI tutors, LLMs can fill knowledge gaps and assess competency in trainees. As chatbots, they can provide empathetic, personalized responses to patient inquiries and improve satisfaction. The visual capabilities of LLMs like GPT-4 allow assisting the visually impaired by describing environments. However, there are significant ethical, technical, and legal challenges around the use of LLMs that should be addressed regarding privacy, fairness, robustness, attribution, and regulation. Ongoing oversight and refinement of models is critical to realize benefits while minimizing risks and upholding responsible AI principles. If carefully implemented, LLMs hold immense potential to push the boundaries of care, discovery, and quality of life for ophthalmology patients.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:39 |
|---|---|
| Enthalten in: |
Seminars in ophthalmology - 39(2024), 4 vom: 08. März, Seite 289-293 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Yaghy, Antonio [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Clinical decision-making |
|---|
| Anmerkungen: |
Date Completed 28.03.2024 Date Revised 28.03.2024 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1080/08820538.2023.2300808 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM366706004 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM366706004 | ||
| 003 | DE-627 | ||
| 005 | 20240329000335.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240108s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1080/08820538.2023.2300808 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1353.xml |
| 035 | |a (DE-627)NLM366706004 | ||
| 035 | |a (NLM)38179986 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Yaghy, Antonio |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Large Language Models in Ophthalmology |b Potential and Pitfalls |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 28.03.2024 | ||
| 500 | |a Date Revised 28.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Large language models (LLMs) show great promise in assisting clinicians in general, and ophthalmology in particular, through knowledge synthesis, decision support, accelerating research, enhancing education, and improving patient interactions. Specifically, LLMs can rapidly summarize the latest literature to keep clinicians up-to-date. They can also analyze patient data to highlight crucial insights and recommend appropriate tests or referrals. LLMs can automate tedious research tasks like data cleaning and literature reviews. As AI tutors, LLMs can fill knowledge gaps and assess competency in trainees. As chatbots, they can provide empathetic, personalized responses to patient inquiries and improve satisfaction. The visual capabilities of LLMs like GPT-4 allow assisting the visually impaired by describing environments. However, there are significant ethical, technical, and legal challenges around the use of LLMs that should be addressed regarding privacy, fairness, robustness, attribution, and regulation. Ongoing oversight and refinement of models is critical to realize benefits while minimizing risks and upholding responsible AI principles. If carefully implemented, LLMs hold immense potential to push the boundaries of care, discovery, and quality of life for ophthalmology patients | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Clinical decision-making | |
| 650 | 4 | |a Large language models (LLMs) | |
| 650 | 4 | |a Ophthalmology | |
| 650 | 4 | |a ethical concerns | |
| 650 | 4 | |a legal concerns | |
| 650 | 4 | |a patient care | |
| 650 | 4 | |a visually impaired | |
| 700 | 1 | |a Yaghy, Maria |e verfasserin |4 aut | |
| 700 | 1 | |a Shields, Jerry A |e verfasserin |4 aut | |
| 700 | 1 | |a Shields, Carol L |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Seminars in ophthalmology |d 1990 |g 39(2024), 4 vom: 08. März, Seite 289-293 |w (DE-627)NLM08584845X |x 1744-5205 |7 nnns |
| 773 | 1 | 8 | |g volume:39 |g year:2024 |g number:4 |g day:08 |g month:03 |g pages:289-293 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1080/08820538.2023.2300808 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 39 |j 2024 |e 4 |b 08 |c 03 |h 289-293 | ||