Joshua Ong

Dr. Joshua Ong


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 February 2024 in Eye
Verified
Journal Article
Open access
PDF file
MMMouayad Masalkhi
Mouayad Masalkhi
Joshua OngJoshua Ong
Joshua Ong
EWEthan Waisberg
Ethan Waisberg
ALAndrew G. Lee
Andrew G. Lee

4 December 2023 in Eye
Verified
Journal Article
Open access
PDF file
EWEthan Waisberg
Ethan Waisberg
Joshua OngJoshua Ong
Joshua Ong
MMMouayad Masalkhi
Mouayad Masalkhi
NZNasif Zaman
Nasif Zaman
PSPrithul Sarker
Prithul Sarker
ATAlireza Tavakkoli
Alireza Tavakkoli

24 July 2023 in Annals of Biomedical Engineering
Verified
Journal Article
Closed access
PDF file
PPPhani Srivatsav Paladugu
Phani Srivatsav Paladugu
Joshua OngJoshua Ong
Joshua Ong
NNNicolas G. Nelson
Nicolas G. Nelson
SKSharif Amit Kamran
Sharif Amit Kamran
EWEthan Waisberg
Ethan Waisberg
ATAlireza Tavakkoli
Alireza Tavakkoli

23 January 2023 in British Journal of Ophthalmology
Verified
Journal Article
Open access
PDF file
Joshua OngJoshua Ong
Joshua Ong
WTWilliam Tarver
William Tarver
TBTyson Brunstetter
Tyson Brunstetter
TMThomas Henry Mader
Thomas Henry Mader
CGC Robert Gibson
C Robert Gibson
ALAndrew G Lee
Andrew G Lee
Spaceflight associated neuro-ocular syndrome (SANS) refers to a distinct constellation of ocular, neurological and neuroimaging findings observed in astronauts during and following long duration spaceflight. These ocular findings, to include optic disc oedema, posterior globe flattening, chorioretinal folds and hyperopic shifts, were first described by NASA in 2011. SANS is a potential risk to astronaut health and will likely require mitigation prior to planetary travel with prolonged exposures to microgravity. While the exact pathogenesis of SANS is not completely understood, several hypotheses have been proposed to explain this neuro-ocular phenomenon. In this paper, we briefly discuss the current hypotheses and contributing factors underlying SANS pathophysiology as well as analogues used to study SANS on Earth. We also review emerging potential countermeasures for SANS including lower body negative pressure, nutritional supplementation and translaminar pressure gradient modulation. Ongoing investigation within these fields will likely be instrumental in preparing and protecting astronaut vision for future spaceflight missions including deep space exploration.

25 August 2022 in npj Microgravity
Verified
Journal Article
Open access
PDF file
Joshua OngJoshua Ong
Joshua Ong
ATAlireza Tavakkoli
Alireza Tavakkoli
NZNasif Zaman
Nasif Zaman
SKSharif Amit Kamran
Sharif Amit Kamran
EWEthan Waisberg
Ethan Waisberg
ALAndrew G Lee
Andrew G Lee
The neuro-ocular effects of long-duration spaceflight have been termed Spaceflight Associated Neuro-Ocular Syndrome (SANS) and are a potential challenge for future, human space exploration. The underlying pathogenesis of SANS remains ill-defined, but several emerging translational applications of terrestrial head-mounted, visual assessment technology and machine learning frameworks are being studied for potential use in SANS. To develop such technology requires close consideration of the spaceflight environment which is limited in medical resources and imaging modalities. This austere environment necessitates the utilization of low mass, low footprint technology to build a visual assessment system that is comprehensive, accessible, and efficient. In this paper, we discuss the unique considerations for developing this technology for SANS and translational applications on Earth. Several key limitations observed in the austere spaceflight environment share similarities to barriers to care for underserved areas on Earth. We discuss common terrestrial ophthalmic diseases and how machine learning and visual assessment technology for SANS can help increase screening for early intervention. The foundational developments with this novel system may help protect the visual health of both astronauts and individuals on Earth.

28 September 2023 in Eye
Verified
Journal Article
Open access
PDF file
EWEthan Waisberg
Ethan Waisberg
Joshua OngJoshua Ong
Joshua Ong
MMMouayad Masalkhi
Mouayad Masalkhi
NZNasif Zaman
Nasif Zaman
PSPrithul Sarker
Prithul Sarker
ATAlireza Tavakkoli
Alireza Tavakkoli
Bard AI, developed by Google, represents a significant advancement in the realm of artificial intelligence (AI) powered chatbots [1]. This innovative AI is designed to simulate human-like interactions, answering a wide array of user inquiries and prompts [1]. Having been trained on a vast dataset of text data, Bard utilizes sophisticated language models to generate comprehensive and informative responses to user inputs [1]. The mechanism behind Bard involves its large language model, specifically the Pathways Language Model 2 (PaLM 2), which has been engineered to excel in comprehending facts, logical reasoning, and mathematics [1]. The capacity of the model to effectively analyze and comprehend contextual information enables it to deliver comprehensive and precise responses to a wide array of inquiries [1, 2]. While Bard shares some similarities with ChatGPT, Bard AI distinguishes itself through its emphasis on factual accuracy. Bard demonstrates exceptional proficiency in understanding and answering questions that require precise information [1]. In contrast, ChatGPT, a generative language model, is proficient in generating creative and diverse types of text, such as articles, code, scripts, and more which may or may not be completely accurate [3]. One of the fundamental differences between Bard AI and ChatGPT lies in their data sources and connections to the internet. Bard AI is linked to Google's expansive search network, granting it access to real-time information from the internet [1]. This allows Bard AI to provide up-to-date information about current events and topics [1]. On the other hand, ChatGPT is not directly connected to the internet, and leverages data up to 2021 to generate its responses [3, 4]. ChatGPT has already shown considerable potential in the field of ophthalmology, from helping triage ophthalmic symptoms [5], medical education [6], answering ophthalmic board certification practice questions [7], writing cataract surgery operative notes [8], developing ophthalmology AI algorithms to classify OCT images [9]. The utilization of Bard AI has considerable potential upside and downside for ophthalmology. The ability of Bard AI to comprehend and provide factual information makes it a valuable tool for