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"Higgins, Kyle"
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The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations
Helicobacter pylori
(
H. pylori
) is the most common carcinogenic pathogen globally and the leading cause of gastric cancer. Here, we develop a reinforcement learning-based AI Clinician system to personalise treatment selection and evaluate its ability to improve eradication success compared to clinician-prescribed therapies. The model is trained and internally validated on 38,049 patients from the retrospective European Registry on
Helicobacter pylori
Management (Hp-EuReg), using independent state deep Q-learning (isDQN) to recommend optimal therapies based on patient characteristics such as age, sex, antibiotic allergies, country, and pre-treatment indication. In internal validation using real-world Hp-EuReg data, AI-recommended therapies achieve a 94.1% success rate (95% CI: 93.2–95.0%) versus 88.1% (95% CI: 87.7–88.4%) for clinician-prescribed therapies not aligned with AI suggestions—an improvement of 6.0%. Results are replicated in an external validation cohort (
n
= 7186), confirming generalisability. The AI system identifies optimal treatment strategies in key subgroups: 65% (
n
= 24,923) are recommended bismuth-based therapies, and 15% (
n
= 5898) non-bismuth quadruple therapies. Random forest modelling identifies region and concurrent medications as patient-specific drivers of AI recommendations. With nearly half the global population likely to contract
H. pylori
, this approach lays the foundation for future prospective clinical validation and shows the potential of AI to support clinical decision-making, enhance outcomes, and reduce gastric cancer burden.
Higgins et al. present an AI tool that uses patient data to personalise treatment for
Helicobacter pylori
, the leading agent of gastric cancer, demonstrating improved eradication rates over prescribed therapies in retrospective clinical analysis.
Journal Article
Nightwing. Volume 4, Second City
\"Kyle Higgins sends Nightwing to the Windy City to track down his parent's killer! After the Joker's attack on the Bat-family, Nightwing finds himself in a new setting with an unlikely ally, The Prankster. Together they are being hunted by the mysterious Mask Killer while Dick tries to find the man who killed his parents, Tony Zullo. Twists and surprises are at every turn in this exciting new chapter of Nightwing! This volume collects Nightwing #19-24\"-- Provided by publisher.
Book
Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes
In the emerging field of computational gastronomy, aligning culinary practices with scientifically supported nutritional goals is increasingly important. This study explores how large language models (LLMs) can be applied to optimize ingredient substitutions in recipes, specifically to enhance the phytochemical content of meals. Phytochemicals are bioactive compounds found in plants, which, based on preclinical studies, may offer potential health benefits. We fine-tuned models, including OpenAI’s GPT-3.5-Turbo, DaVinci-002, and Meta’s TinyLlama-1.1B, using an ingredient substitution dataset. These models were used to predict substitutions that enhance the phytochemical content and to create a corresponding enriched recipe dataset. Our approach improved the top ingredient prediction accuracy on substitution tasks, from the baseline 34.53 ± 0.10% to 38.03 ± 0.28% on the original substitution dataset and from 40.24 ± 0.36% to 54.46 ± 0.29% on a refined version of the same dataset. These substitutions led to the creation of 1951 phytochemically enriched ingredient pairings and 1639 unique recipes. While this approach demonstrates potential in optimizing ingredient substitutions, caution must be taken when drawing conclusions about health benefits, as the claims are based on preclinical evidence. This research represents a step forward in using AI to promote healthier eating practices, providing potential pathways for integrating computational methods with nutritional science.
Journal Article
Nightwing. Volume 1, Traps and trapezes
Dick Grayson, Batman's former ward, must now embrace his destiny alone as the high-flyer Nightwing. Haly's Circus, where Dick grew up and performed under the big top, returns to Gotham City, bringing with it murder, mystery and superhuman mayhem.
Book
Foundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation
The integration of artificial intelligence (AI) in medical diagnostics represents a significant advancement in managing upper gastrointestinal (GI) cancer, which is a major cause of global cancer mortality. Specifically for gastric cancer (GC), chronic inflammation causes changes in the mucosa such as atrophy, intestinal metaplasia (IM), dysplasia, and ultimately cancer. Early detection through endoscopic regular surveillance is essential for better outcomes. Foundation models (FMs), which are machine or deep learning models trained on diverse data and applicable to broad use cases, offer a promising solution to enhance the accuracy of endoscopy and its subsequent pathology image analysis. This review explores the recent advancements, applications, and challenges associated with FMs in endoscopy and pathology imaging. We started by elucidating the core principles and architectures underlying these models, including their training methodologies and the pivotal role of large-scale data in developing their predictive capabilities. Moreover, this work discusses emerging trends and future research directions, emphasizing the integration of multimodal data, the development of more robust and equitable models, and the potential for real-time diagnostic support. This review aims to provide a roadmap for researchers and practitioners in navigating the complexities of incorporating FMs into clinical practice for the prevention/management of GC cases, thereby improving patient outcomes.
Journal Article
Nightwing : the new order
\"Author Kyle Higgins presents a near-future world where society has completely rejected superpowers. Metahumans are illegal and none-other than the former Boy Wonder heads a government sponsered task force to hunt them down. But what do you do when your own son becomes illicit in the very system you helped create? This new \"Elseworlds\"-style tale is a must-own for any fan of Nightwing!\"-- Provided by publisher.
Book
Agrivoltaics: Modeling the relative importance of longwave radiation from solar panels
Agrivoltaics, which integrate photovoltaic power production with agriculture in the same plot of land, have the potential to reduce land competition, reduce crop irrigation, and increase solar panel efficiency. To optimize agrivoltaic systems for crop growth, energy pathways must be characterized. While the solar panels shade the crops, they also emit longwave radiation and partially block the ground from downwelling longwave radiation. A deeper understanding of the spatial variation in incoming energy would enable controlled allocation of energy in the design of agrivoltaic systems. The model also demonstrates that longwave energy should not be neglected when considering a full energy balance on the soil under solar panels.
Journal Article
Batman : gates of Gotham
\"At the turn of the century, three prominent families shaped the construction of modern-day Gotham City. Now a madman with 300 pounds of explosives and a century-old grudge is threatening to bring it all crashing down. Beginning with the simultaneous destruction of some of Gotham's oldest bridges, the mysterious villain is targeting the holdings and legacies of Gotham's most notable families--including the Waynes. To uncover the truth behind the villainous Architect and his link to the city's violent past, Batman unites with Robin, Red Robin and Batman Inc.'s Hong Kong operative, the Black Bat. But can they stop their new foe's plans before it's too late? The future of Gotham started with an explosion, and it could end the very same way.\"-- Provided by publisher.
Book
Trends in High-grade Cervical Lesions and Cervical Cancer Screening in 5 States, 2008–2015
We describe trends in high-grade cervical lesions (CIN2+), identified through population-based surveillance in 2008–2015. In addition to changed screening recommendations, observed CIN2+ declines among screened women aged 18–24 years indicate a population-level impact of human papillomavirus vaccination.
Abstract
Background
We describe changes in rates of cervical intraepithelial neoplasia grades 2, 3 and adenocarcinoma in situ (CIN2+) during a period of human papillomavirus (HPV) vaccine uptake and changing cervical cancer screening recommendations.
Methods
We conducted population-based laboratory surveillance for CIN2+ in catchment areas in 5 states, 2008–2015. We calculated age-specific CIN2+ rates per 100000 women by age groups. We estimated incidence rate ratios (IRR) of CIN2+ for 2-year periods among all women and among screened women to evaluate changes over time.
Results
A total of 16572 CIN2+ cases were reported. Among women aged 18–20 and 21–24 years, CIN2+ rates declined in all sites, whereas in women aged 25–29, 30–34, and 35–39 years, trends differed across sites. The percent of women screened annually declined in all sites and age groups. Compared to 2008–2009, rates among screened women were significantly lower for all 3 periods in women aged 18–20 years (2010–2011: IRR 0.82, 95% confidence interval [CI] 0.67–0.99; 2012–2013: IRR 0.63, 95% CI 0.47–0.85; 2014–2015: IRR 0.44, 95% CI 0.28–0.68) and lower for the latter 2 time periods in women aged 21–24 years (2012–2013: IRR 0.86, 95% CI 0.79–0.94; 2014–2015: IRR 0.61, 95% CI 0.55–0.67).
Conclusions
From 2008–2015, both CIN2+ rates and cervical cancer screening declined in women aged 18–24 years. The significant decreases in CIN2+ rates among screened women aged 18–24 years are consistent with a population-level impact of HPV vaccination.
Journal Article