One book by Rubin talks about holding up a Playboy centerfold in front of the person faking blindness and the patient laughed and said “you got me”.

At least it wasn’t a New Coke.

All humans descended from one woman named Eve, based on mitochondrial DNA. All males descended from one man named Adam, based on Y chromosome DNA. But This Adam and this Eve never met.

I hope it was NOT an eye doctor!

So are you saying they did in fact take over the world?

Hyperbaric oxygen is not indicated for ADHD. Who was the doctor who prescribed this?

Here's what it says in the study:

"The ophthalmologist-in-training makes these triage decisions based on their clinical training, medical knowledge, and judgment. The General Eye Clinic is overseen by an attending ophthalmologist. If the ophthalmologist-in-training has questions about triage recommendations, an attending is available to consult."

So, I think the ophthalmologist-in-training was asking the attendings questions in real time if they had questions--not after the fact.

I would think of it as a comparison of Chat GPT with what a university ophthalmology department actually does. Here the university has residents answer the triage, unless they think they need help, in which case they ask an attending for help. They also might ask an attending of whatever specialty is appropriate--e.g. retina, glaucoma, pediatrics, cornea, etc.--to answer the question if they are not sure.

It is hard to know what is correct. Different eye doctors might not agree. The report does list examples in which Chat GPT was less conservative than the ophthalmologist-in-training, and the reader can decide if they agree more with Chat GPT or with the ophthalmologist-in-training, because for these examples the final diagnosis is provided. Generally, Chat GPT asked the patient to come in sooner than the ophthalmologist (when there was a disagreement).

This study compared what the residents actually did with ChatGPT. It wasn't what residents said in an experimental situation. And actually, the residents could check with the attendings if they had any questions, so it was really a system that included attendings as back-up.

Yes, just normal Chat GPT.

Background/Objectives: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general eye clinic at our institution. 

Methods: Patient messages sent to the general eye clinic via MyChart were de-identified and then triaged by an ophthalmologist-in-training (MD) as well as GPT-4 with two main objectives. Both MD and GPT-4 were asked to direct patients to either general or specialty eye clinics, urgently or nonurgently, depending on the severity of the condition. Main Outcomes: GPT-4s ability to accurately direct patient messages to (1) a general or specialty eye clinic and (2) determine the time frame within which the patient needed to be seen (triage acuity). Accuracy was determined by comparing percent agreement with recommendations given by GPT-4 with those given by MD. 

Results: The study included 139 messages. Percent agreement between the ophthalmologist-in-training and GPT-4 was 64.7% for general/specialty clinic recommendation and 60.4% for triage acuity. Cohen’s kappa was 0.33 and 0.67 for specialty clinic and triage urgency, respectively. GPT-4 recommended a triage acuity equal to or sooner than ophthalmologist-in-training for 93.5% of cases and recommended a less urgent triage acuity in 6.5% of cases. 

Conclusions: Our study indicates an AI system, such as GPT-4, should complement rather than replace physician judgment in triaging ophthalmic complaints. These systems may assist providers and reduce the workload of ophthalmologists and ophthalmic technicians as GPT-4 becomes more adept at triaging ophthalmic issues. Additionally, the integration of AI into ophthalmic triage could have therapeutic implications by ensuring timely and appropriate care, potentially improving patient outcomes by reducing delays in treatment. Combining GPT-4 with human expertise can improve service delivery speeds and patient outcomes while safeguarding against potential AI pitfalls.

Background/Objectives: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general eye clinic at our institution. 

Methods: Patient messages sent to the general eye clinic via MyChart were de-identified and then triaged by an ophthalmologist-in-training (MD) as well as GPT-4 with two main objectives. Both MD and GPT-4 were asked to direct patients to either general or specialty eye clinics, urgently or nonurgently, depending on the severity of the condition. Main Outcomes: GPT-4s ability to accurately direct patient messages to (1) a general or specialty eye clinic and (2) determine the time frame within which the patient needed to be seen (triage acuity). Accuracy was determined by comparing percent agreement with recommendations given by GPT-4 with those given by MD. 

Results: The study included 139 messages. Percent agreement between the ophthalmologist-in-training and GPT-4 was 64.7% for general/specialty clinic recommendation and 60.4% for triage acuity. Cohen’s kappa was 0.33 and 0.67 for specialty clinic and triage urgency, respectively. GPT-4 recommended a triage acuity equal to or sooner than ophthalmologist-in-training for 93.5% of cases and recommended a less urgent triage acuity in 6.5% of cases. 

Conclusions: Our study indicates an AI system, such as GPT-4, should complement rather than replace physician judgment in triaging ophthalmic complaints. These systems may assist providers and reduce the workload of ophthalmologists and ophthalmic technicians as GPT-4 becomes more adept at triaging ophthalmic issues. Additionally, the integration of AI into ophthalmic triage could have therapeutic implications by ensuring timely and appropriate care, potentially improving patient outcomes by reducing delays in treatment. Combining GPT-4 with human expertise can improve service delivery speeds and patient outcomes while safeguarding against potential AI pitfalls.

Background/Objectives: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general eye clinic at our institution. 

Methods: Patient messages sent to the general eye clinic via MyChart were de-identified and then triaged by an ophthalmologist-in-training (MD) as well as GPT-4 with two main objectives. Both MD and GPT-4 were asked to direct patients to either general or specialty eye clinics, urgently or nonurgently, depending on the severity of the condition. Main Outcomes: GPT-4s ability to accurately direct patient messages to (1) a general or specialty eye clinic and (2) determine the time frame within which the patient needed to be seen (triage acuity). Accuracy was determined by comparing percent agreement with recommendations given by GPT-4 with those given by MD. 

Results: The study included 139 messages. Percent agreement between the ophthalmologist-in-training and GPT-4 was 64.7% for general/specialty clinic recommendation and 60.4% for triage acuity. Cohen’s kappa was 0.33 and 0.67 for specialty clinic and triage urgency, respectively. GPT-4 recommended a triage acuity equal to or sooner than ophthalmologist-in-training for 93.5% of cases and recommended a less urgent triage acuity in 6.5% of cases. 

Conclusions: Our study indicates an AI system, such as GPT-4, should complement rather than replace physician judgment in triaging ophthalmic complaints. These systems may assist providers and reduce the workload of ophthalmologists and ophthalmic technicians as GPT-4 becomes more adept at triaging ophthalmic issues. Additionally, the integration of AI into ophthalmic triage could have therapeutic implications by ensuring timely and appropriate care, potentially improving patient outcomes by reducing delays in treatment. Combining GPT-4 with human expertise can improve service delivery speeds and patient outcomes while safeguarding against potential AI pitfalls.

Is it really a pet rabbit if it’s a working magic rabbit?

It’s in Dickens.

The people who are crazy enough to think they can cross thousands of miles of ocean to find an island paradise are the ones who do.

Purpose: Most ophthalmologists in the United States recognize the name "Bascom Palmer" but few are familiar with the individual for whom the Eye Institute is named. This article reviews the biography of Bascom Headen Palmer, Jr, MD (1889-1954).

Design: Historical review.

Methods: Historical documents were reviewed, including the archives of the University of Miami, the Miami Lighthouse for the Blind and Visually Impaired, and other sources.

Results: Palmer, born in Lake City, Florida in 1889, was the younger son of a Florida politician. He graduated from what was then called the College of Medicine of the Tulane University of Louisiana (now the Tulane University School of Medicine) in 1914, followed by a 2-year internship at Touro Infirmary, service in the army during World War I, and finally a postgraduate course in ophthalmology at the University of Pennsylvania in 1923. He then moved to Miami, where he became influential in 2 new organizations: the University of Miami, founded in 1925, and the Florida Association of Workers for the Blind (now the Miami Lighthouse for the Blind and Visually Impaired), founded in 1930. He forged collaborations between these 2 organizations which eventually led to the foundation of the eponymous Eye Institute.

Conclusions: The decades-long collaboration between the Miami Lighthouse and the University of Miami, facilitated by Palmer, ultimately led to the founding of the Eye Institute.

A horse 

Young Sheldon was overshadowed by George and Mandy’s relationship.