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  • AI & Machine Learning, Biology, Computing, Data & AI, Life Sciences
    Syn4MD: Aiding Medical Diagnosis through Image Synthesis and Classification
    Abstract Medical trainees depend on diverse visual reference material to develop diagnostic pattern-recognition skills, yet such material is often limited in diversity and accessibility. This paper presents a classifier-in-the-loop generative framework for synthesising realistic histopathology images: a Stable Diffusion v1.5 model is fine-tuned using Low-Rank Adaptation (LoRA) on the PathMNIST dataset, consisting of nine colorectal […]
    Kanishk Choudhary
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    August 3, 2026
  • Biology, Chemistry, Life Sciences, Physical Sciences
    DiaBreath: Multivariate Analysis of a Non-Selective Low-Cost Metal Oxide (MOX) Sensor Array for Breath-Based Diabetes Screening
    Abstract The number of diabetes patients is increasing worldwide, but many cases stay undiagnosed in low-resource regions. The A1C blood test is invasive and costly, therefore it is often not available in these regions. In this research, DiaBreath is proposed as a low-cost noninvasive screening system based on exhaled breath analysis. Volatile organic compounds (VOCs) […]
    Woo Sung Choi
    |
    July 24, 2026
  • Computing, Data & AI, Data Science, Economics, Social Sciences, Humanities & Policy
    A Statistical Physics Approach to Market Dynamics: Regime Shifts in Digital vs. Local Vendor Choice
    Abstract Digital commerce platforms compete with local vendors under frictions of time, price, and visibility. We test whether an interpretable choice model with reinforcement and social influence can yield substantial changes in aggregate market share as control parameters vary. We simulate repeated customer choice among vendors using a utility function that combines vendor attributes (price, […]
    Amaira Goyal
    |
    July 12, 2026
  • AI & Machine Learning, Computing, Data & AI
    Predicting Limited Service Zones Using GIS-Integrated Machine Learning: A Case Study of Three Cities
    Abstract Local businesses are important to neighborhood service access, but access to these services is limited in some areas. This study uses GIS and machine learning to identify possible limited service zones for restaurants and supermarkets across Dublin, Pleasanton, and Livermore in Alameda County, California. The model dataset included 1,134 Alameda County census block groups, […]
    Mandy Yuan
    |
    July 8, 2026

Most Discussed ›

NHSJS Reports ›

Life Sciences ›

  • AI & Machine Learning, Computing, Data & AI, Life Sciences, Neuroscience
    Deep Learning Classification of Psychiatric Disorders from Resting-State EEG: A Multi-Disorder Study Using the TDBRAIN Dataset
    Abstract Background: Modern diagnosis of psychiatric disorders often includes subjective techniques across clinicians, such as interviews and the self-reporting of symptoms, which yield inconsistent results. However, Electroencephalography (EEG) can complement these current methods, offering a non-invasive and standardized measurement of biological signals. This study evaluates the accuracy of deep learning models in classification of psychiatric […]
    Aashni Katari
    |
    October 23, 2026

Health Sciences ›

Physical Sciences ›

  • Astronomy & Astrophysics, Physical Sciences
    Computational Study of Black Hole Shadows Using Ray Tracing
    Abstract This paper uses a computational approach to study the geometry of black hole shadows under precisely controlled conditions. It uses a non-rotating Schwarzschild case as a baseline and extends to a rotating Kerr metric to examine the effect of spin on the geometry. The simulated shadows are then analyzed with quantities representing left–right asymmetry […]
    Do Hoang Giang
    |
    October 22, 2026

Computing, Data & AI ›

  • AI & Machine Learning, Computer Science, Computing, Data & AI
    When Should Multi-Agent Debate Stop? A Comparison of Fixed-Round and Adaptive Stopping
    Abstract In a multi-agent debate, language-model agents discuss their responses before the system chooses a final answer. Each additional round requires more inference-time computation. We examined whether setting a confidence threshold would reduce unneeded debate rounds while maintaining answer accuracy. We tested fixed-round and adaptive schedules in the publicly available Du and Liang frameworks. Each […]
    Avik Shekhar
    |
    October 25, 2026

Engineering ›

  • AI & Machine Learning, Biomedical Engineering, Computing, Data & AI, Engineering
    Deep Learning Biomedical Application: Finger Movement Recognition Through Time Series Classification of Electromyographic Signals
    Abstract Electromyographic (EMG) signal classification is vital but remains challenging for advanced prosthetics and medical diagnostics, especially when the number of movement classes increases. While the field favors convolutional neural networks (CNNs), they require more computational resources than small prosthetic devices can handle. Thus, we compared CNNs with simpler feedforward neural networks (FFNNs) to explore […]
    Nana Fukushima
    |
    October 21, 2026

Earth & Environment ›

Mathematics & Statistics ›

Social Sciences, Humanities & Policy ›

  • Social Sciences, Social Sciences, Humanities & Policy
    Economic Barriers to Family Formation and Demographic Trends in Smolensk Oblast: A Pilot Survey of High-School Students
    Abstract The Smolensk Oblast faces persistent demographic decline, with birth rates falling from 10.6‰ in 2015 to 5.8‰ in 2023 and sustained youth out-migration to more developed regions. Despite federal and regional family support programs, these trends continue. This pilot study explores whether economic barriers (income and housing) are perceived as more significant obstacles to […]
    Egor Udra, Artem Sekachev
    |
    October 18, 2026

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