Applications of interpretability in deep learning models for ophthalmology

PURPOSE OF REVIEW: In this article, we introduce the concept of model interpretability, review its applications in deep learning models for clinical ophthalmology, and discuss its role in the integration of artificial intelligence in healthcare. RECENT FINDINGS: The advent of deep learning in medicine has introduced models with remarkable accuracy. However, the inherent complexity of these models undermines its users' ability to understand, debug and ultimately trust them in clinical practice. Novel methods are being increasingly explored to improve models' 'interpretability' and draw clearer associations between their outputs and features in the input dataset. In the field of ophthalmology, interpretability methods have enabled users to make informed adjustments, identify clinically relevant imaging patterns, and predict outcomes in deep learning models. SUMMARY: Interpretability methods support the transparency necessary to implement, operate and modify complex deep learning models. These benefits are becoming increasingly demonstrated in models for clinical ophthalmology. As quality standards for deep learning models used in healthcare continue to evolve, interpretability methods may prove influential in their path to regulatory approval and acceptance in clinical practice

Generative adversarial networks in ophthalmology: what are these and how can they be used?

PURPOSE OF REVIEW: The development of deep learning (DL) systems requires a large amount of data, which may be limited by costs, protection of patient information and low prevalence of some conditions. Recent developments in artificial intelligence techniques have provided an innovative alternative to this challenge via the synthesis of biomedical images within a DL framework known as generative adversarial networks (GANs). This paper aims to introduce how GANs can be deployed for image synthesis in ophthalmology and to discuss the potential applications of GANs-produced images. RECENT FINDINGS: Image synthesis is the most relevant function of GANs to the medical field, and it has been widely used for generating 'new' medical images of various modalities. In ophthalmology, GANs have mainly been utilized for augmenting classification and predictive tasks, by synthesizing fundus images and optical coherence tomography images with and without pathologies such as age-related macular degeneration and diabetic retinopathy. Despite their ability to generate high-resolution images, the development of GANs remains data intensive, and there is a lack of consensus on how best to evaluate the outputs produced by GANs. SUMMARY: Although the problem of artificial biomedical data generation is of great interest, image synthesis by GANs represents an innovation with yet unclear relevance for ophthalmology

Generative Artificial Intelligence Through ChatGPT and Other Large Language Models in Ophthalmology: Clinical Applications and Challenges

The rapid progress of large language models (LLMs) driving generative artificial intelligence applications heralds the potential of opportunities in health care. We conducted a review up to April 2023 on Google Scholar, Embase, MEDLINE, and Scopus using the following terms: “large language models,” “generative artificial intelligence,” “ophthalmology,” “ChatGPT,” and “eye,” based on relevance to this review. From a clinical viewpoint specific to ophthalmologists, we explore from the different stakeholders’ perspectives—including patients, physicians, and policymakers—the potential LLM applications in education, research, and clinical domains specific to ophthalmology. We also highlight the foreseeable challenges of LLM implementation into clinical practice, including the concerns of accuracy, interpretability, perpetuating bias, and data security. As LLMs continue to mature, it is essential for stakeholders to jointly establish standards for best practices to safeguard patient safety. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

Radio pulsar populations

The goal of this article is to summarize the current state of play in the field of radio pulsar statistics. Simply put, from the observed sample of objects from a variety of surveys with different telescopes, we wish to infer the properties of the underlying sample and to connect these with other astrophysical populations (for example supernova remnants or X-ray binaries). The main problem we need to tackle is the fact that, like many areas of science, the observed populations are often heavily biased by a variety of selection effects. After a review of the main effects relevant to radio pulsars, I discuss techniques to correct for them and summarize some of the most recent results. Perhaps the main point I would like to make in this article is that current models to describe the population are far from complete and often suffer from strong covariances between input parameters. That said, there are a number of very interesting conclusions that can be made concerning the evolution of neutron stars based on current data. While the focus of this review will be on the population of isolated Galactic pulsars, I will also briefly comment on millisecond and binary pulsars as well as the pulsar content of globular clusters and the Magellanic Clouds.Comment: 16 pages, 6 figures, to appear in Proceedings of ICREA Workshop on The High-Energy Emission from Pulsars and their Systems, Sant Cugat, Spain, 2010 April 12-16 (Springer

Political Self-characterization of U.S. Medical Students

BACKGROUND: There have been no prior studies of the political self-characterization of U.S. physicians-in-training, and little is known about physicians’ political leanings or the critical relationship between medical issues and political orientations of physicians and physicians-in-training. METHODS: All medical students in the class of 2003 at 16 nationally representative U.S. schools were eligible to complete three questionnaire administrations (at freshman orientation, entrance to wards, and senior year). RESULTS: Among these medical students, 5% self-characterized as politically very conservative, 21% conservative, 33% moderate, 31% liberal, and 9% as very liberal.” Being male, white, Protestant, intending to specialize in Surgery or anesthesiology/pathology/radiology, or currently or previously being married significantly (P ≤ .001) increased the likelihood that a student self-identified as very conservative or conservative. Disagreement or strong disagreement with the statements, “I’m glad I chose to become a physician” and “Access to care is a fundamental human right,” were also both associated with being very conservative or conservative. Being more liberal was reported by blacks and Hispanics; those intending to become ob-gyns, psychiatrists, and pediatric subspecialists; and atheists, Jews, and adherents of eastern religions. CONCLUSIONS: U.S. medical students are considerably more likely to be liberal than conservative and are more likely to be liberal than are other young U.S. adults. Future U.S. physicians may be more receptive to liberal messages than conservative ones, and their political orientation may profoundly affect their health system attitudes

Monitoring one-electron photo-oxidation of guanine in DNA crystals using ultrafast infrared spectroscopy

To understand the molecular origins of diseases caused by ultraviolet and visible light, and also to develop photodynamic therapy, it is important to resolve the mechanism of photoinduced DNA damage. Damage to DNA bound to a photosensitizer molecule frequently proceeds by one-electron photo-oxidation of guanine, but the precise dynamics of this process are sensitive to the location and the orientation of the photosensitizer, which are very difficult to define in solution. To overcome this, ultrafast time-resolved infrared (TRIR) spectroscopy was performed on photoexcited ruthenium polypyridyl–DNA crystals, the atomic structure of which was determined by X-ray crystallography. By combining the X-ray and TRIR data we are able to define both the geometry of the reaction site and the rates of individual steps in a reversible photoinduced electron-transfer process. This allows us to propose an individual guanine as the reaction site and, intriguingly, reveals that the dynamics in the crystal state are quite similar to those observed in the solvent medium