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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
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    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
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    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 ›

  • Biology, Life Sciences
    Preliminary In Vitro Screening of Aqueous Taraxacum Officinale and Coptis Chinensis Extracts against Selected Aerobically Culturable Facial Skin Isolates
    Abstract The human facial epidermis is inhabited by a complex and heterogeneous microecosystem. The antibiotic therapy is a usual way to treat the bacterial dermatological infections, however, the long application of them generally results the appearance of the drug resistant strains. In addition, such long application can destroy the balance of the native facial microbiota […]
    Yuchen Liang
    |
    October 28, 2026
  • Bioinformatics, Life Sciences
    LIANA+ Inferred Cell-Cell Interaction Analysis Reveals Differences in SLE-Associated Immune Cell Communication Between Pediatric and Adult Cohorts
    Abstract Systemic lupus erythematosus (SLE) differs between pediatric and adult populations, but cohort differences in inferred immune-cell communication remain uncertain. We reanalyzed GSE135779, retaining 298,610 peripheral blood mononuclear cells from 56 donors: 33 pediatric SLE, 11 pediatric healthy, seven adult SLE, and five adult healthy. Donor-level LIANA+ relative communication scores were analyzed using a disease-by-cohort […]
    Aaron Choi
    |
    October 28, 2026
  • AI & Machine Learning, Computing, Data & AI, Health Sciences, Public Health
    Symptom-Based Disease Prediction Using a T5 Transformer Model
    Abstract Correctly diagnosing diseases from patient-reported symptoms is challenging due to vague and overlapping symptom descriptions. In this study, we evaluated whether a fine-tuned T5-small transformer model could accurately predict diseases from natural-language symptom descriptions. We hypothesized that training a lightweight sequence-to-sequence model on a structured symptom–disease dataset reformatted into text-based prompts would achieve high […]
    Aanvi Manda
    |
    October 28, 2026
  • Health Sciences, Life Sciences, Neuroscience, Psychology
    The Role of Quantifiable Affordances in Adolescents’ Neural Sensitivity to Social Evaluation and Self-Esteem: A Narrative Literature Review
    Abstract The rise of social media in recent years has led to increased usage, particularly among adolescents, who represent key users of these platforms. Because adolescence is a critical period for neurodevelopment, social media exposure during this time may influence developmental processes that shape cognitive and behavioral outcomes. These developmental patterns  have been associated with […]
    Kotoha Sakamoto
    |
    October 28, 2026
  • Electrical Engineering, Engineering
    Design and Characterization of an Ultrasonic Time-to-Collision Trigger for Bird-Glass Warning Applications
    Abstract Hundreds of millions of birds are estimated to be killed each year by flying into the windows of buildings across America. Passive protective measures such as decals and patterned films have been used to protect birds; however, their use is inconsistent. Sensor-based active mitigation systems are being evaluated in wind-energy facilities, but their application […]
    Alison Li
    |
    October 27, 2026

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 ›

Computing, Data & AI ›

Engineering ›

  • Engineering, Mechanical Engineering
    Modeling Temporal Dynamics for Cavitation-Induced Valve Plate Failure Detection in Hydraulic Pumps
    Abstract This study investigates the use of machine learning for fault detection of cavitation-induced valve plate failures in hydraulic piston pumps using multivariate sensor data. We compared  non-sequential models with engineered lagged features to sequence-based deep learning models that explicitly include temporal dependencies using an established experimental dataset. Long Short-Term Memory (LSTM) networks achieved the […]
    Aidan Lee
    |
    October 28, 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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