machine learning

  1. forestglip

    Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset, 2024, Hällqvist et al

    Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset Jenny Hällqvist, Michael Bartl, Mohammed Dakna, Sebastian Schade, Paolo Garagnani, Maria-Giulia Bacalini, Chiara Pirazzini, Kailash Bhatia, Sebastian Schreglmann, Mary Xylaki, Sandrina Weber...
  2. SNT Gatchaman

    The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome, 2024, Su et al.

    The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome Qi Su; Raphaela I. Lau; Qin Liu; Moses K.T. Li; Joyce Wing Yan Mak; Wenqi Lu; Ivan S.F. Lau; Louis H.S. Lau; Giann T.Y. Yeung; Chun Pan Cheung; Whitney Tang; Chengyu Liu; Jessica Y.L. Ching; Pui Kuan...
  3. SNT Gatchaman

    Preprint Exploring Metabolic Anomalies in COVID-19 and Post-COVID-19: A Machine Learning Approach, 2024, Oropeza-Valdez et al.

    Exploring Metabolic Anomalies in COVID-19 and Post-COVID-19: A Machine Learning Approach with Explainable Artificial Intelligence Juan José Oropeza-Valdez; Cristian Padron-Manrique; Aaron Vazquez-Jimenez; Xavier Soberon-Mainero; Osbaldo Resendis-Antonio The COVID-19 pandemic, caused by...
    • SNT Gatchaman
    • Thread
    • artificial intelligence glutamine kynurenine lactate long covid machine learning metabolic reprogramming metabolomics phenylalanine pyruvate spermidine taurine tryptophan
    • Replies: 1
    • Forum: Long Covid research
  4. SNT Gatchaman

    Exploring Cognitive Dysfunction in LC Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications, 2024, Benito-León+

    Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning Julián Benito-León; José Lapeña; Lorena García-Vasco; Constanza Cuevas; Julie Viloria-Porto; Alberto Calvo-Córdoba; Estíbaliz...
  5. SNT Gatchaman

    Increased Angio-Derived Index of Microcirculatory Resistance Within a Timeframe of 30–60 days After COVID-19 Infection, 2024, Dong et al.

    Increased Angio-Derived Index of Microcirculatory Resistance Within a Timeframe of 30–60 days After COVID-19 Infection Lei Dong; Ritai Na; Lang Peng; Xinye Xu BACKGROUND AND OBJECTIVES Chest pain is a relatively long-term symptom that commonly occurs in patients who have contracted COVID-19...
    • SNT Gatchaman
    • Thread
    • cardiac cardiac syndrome x coronary arteries long covid machine learning microcirculation microvascular dysfunction
    • Replies: 4
    • Forum: Long Covid research
  6. SNT Gatchaman

    “AI will cure cancer” misunderstands both AI and medicine

    by Rachel Thomas, PhD (Discusses long Covid, systemic medical failures and misdiagnoses) https://rachel.fast.ai/posts/2024-02-20-ai-medicine/
  7. SNT Gatchaman

    PubMed and beyond: biomedical literature search in the age of artificial intelligence, 2024, Jin et al.

    PubMed and beyond: biomedical literature search in the age of artificial intelligence Qiao Jin; Robert Leaman; Zhiyong Lu Biomedical research yields vast information, much of which is only accessible through the literature. Consequently, literature search is crucial for healthcare and...
  8. ME/CFS Skeptic

    Achievements of Artificial Intelligence (AI)

    I thought it might be useful to create a thread to organize news on what Artificial Intelligence is able to achieve. Its applications might be useful for ME/CFS advocacy and research.
  9. SNT Gatchaman

    Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling, 2023, Saunders et al.

    Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling Nell Saunders; Blandine Monel; Nadege Cayet; Lorenzo Archetti; Hugo Moreno; Alexandre Jeanne; Agathe Marguier; Timothy Wai; Olivier Schwartz; Mathieu Frechin Assessing the impact of SARS-CoV-2 on...
  10. SNT Gatchaman

    Preprint From Data to Insights: Machine Learning Empowers Prognostic Biomarker Prediction in Autism, 2023, Mehmetbeyoglu et al.

    From Data to Insights: Machine Learning Empowers Prognostic Biomarker Prediction in Autism Ecmel Mehmetbeyoglu; Abdulkerim Duman; Serpil Taheri; Yusuf Ozkul; Minoo Rassoulzadegan Autism Spectrum Disorder (ASD) poses significant challenges to society and science due to its impact on...
  11. SNT Gatchaman

    Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry, 2023, Bendella et al.

    Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry Bendella, Zeynep; Widmann, Catherine Nichols; Layer, Julian Philipp; Layer, Yonah Lucas; Haase, Robert; Sauer, Malte; Bieler, Luzie; Lehnen, Nils Christian; Paech, Daniel; Heneka...
  12. SNT Gatchaman

    Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease, 2023, Wagner et al.

    Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease Siegfried Karl Wagner; David Romero-Bascones; Mario Cortina-Borja; Dominic J Williamson; Robbert R Struyven; Yukun Zhou; Salil Patel; Rimona S Weil; Chrystalina A Antoniades; Eric J Topol...
  13. J

    Preprint A Proposed Explainable Artificial Intelligence-Based Machine Learning Model for Discriminative Metabolites for ME/CFS, 2023, Yagin et al

    Full title: A Proposed Explainable Artificial Intelligence-Based Machine Learning Model for Discriminative Metabolites for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Abstract Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating disease...
    • John Mac
    • Thread
    • artificial intelligence machine learning me/cfs metabolites
    • Replies: 9
    • Forum: ME/CFS research
  14. SNT Gatchaman

    Preprint EpiGePT: a Pretrained Transformer model for epigenomics, 2023, Gao et al.

    EpiGePT: a Pretrained Transformer model for epigenomics Zijing Gao; Qiao Liu; Wanwen Zeng; Wing H Wong; Rui Jiang The transformer-based models, such as GPT-31 and DALL-E2, have achieved unprecedented breakthroughs in the field of natural language processing and computer vision. The inherent...
  15. RedFox

    Artificial intelligence in medicine and science

    Glass AI--AI that generates differential diagnosis and clinical plans Recently I learned about this AI tool, which is currently available for anyone to use without cost or registration. Edit: Darn I forgot the link: https://glass.health/ai I'm playing around with it to see how well it...
  16. SNT Gatchaman

    Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes, 2022, Zhang et al

    Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes Hao Zhang, Chengxi Zang, Zhenxing Xu, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Dhruv Khullar, Yiye Zhang, Anna S. Nordvig, Edward J. Schenck, Elizabeth A. Shenkman, Russell L. Rothman, Jason P. Block, Kristin...
  17. cassava7

    New Scientist: DeepMind's protein-folding AI cracks biology's biggest problem, 2022

    Artificial intelligence firm DeepMind has transformed biology by predicting the structure of nearly all proteins known to science in just 18 months, a breakthrough that will speed drug development and revolutionise basic science. DeepMind has predicted the structure of almost every protein so...
  18. Sly Saint

    Brain predictors of fatigue in rheumatoid arthritis: A machine learning study, 2022, Goni et al

    Abstract Background Fatigue is a common and burdensome symptom in Rheumatoid Arthritis (RA), yet is poorly understood. Currently, clinicians rely solely on fatigue questionnaires, which are inherently subjective measures. For the effective development of future therapies and stratification, it...
  19. Andy

    Objective Diagnosis of Fibromyalgia Using Neuroretinal Evaluation and Artificial Intelligence, 2022, Boquetea et al

    Abstract Background/Objective This study aims to identify objective biomarkers of fibromyalgia (FM) by applying artificial intelligence algorithms to structural data on the neuroretina obtained using swept-source optical coherence tomography (SS-OCT). Method The study cohort comprised 29 FM...
  20. SNT Gatchaman

    Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning, Mueller, 2022

    Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning Yvonne M. Mueller, Thijs J. Schrama, Rik Ruijten, Marco W. J. Schreurs, Dwin G. B. Grashof, Harmen J. G. van de Werken, Giovanna Jona Lasinio, Daniel...
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