Article List
List all articles in the database by earliest discovery_date
GET /articles/?format=api
{ "count": 20746, "next": "http://api.gregory-ms.com/articles/?format=api&page=2", "previous": null, "results": [ { "article_id": 67546, "title": "Cumulative exposure to high remnant-cholesterol concentrations increases the risk of cardiovascular disease in patients with hypertension: a prospective cohort study", "summary": null, "link": "https://cardiab.biomedcentral.com/articles/10.1186/s12933-023-01984-4", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T23:32:55.608654Z", "noun_phrases": [ "Cumulative exposure", "high remnant-cholesterol concentrations", "the risk", "cardiovascular disease", "patients", "hypertension", "a prospective cohort study" ], "doi": "10.1186/s12933-023-01984-4", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67496, "title": "Invited Session V: The eye as a window to systemic and neurodegenerative health: Early prediction of multiple sclerosis using scanning laser ophthalmoscopy (SLO) video sequence data with a Deep Learning (DL) based approach", "summary": "<div><p>J Vis. 2023 Sep 1;23(11):29. doi: 10.1167/jov.23.11.29.</p><p><b>ABSTRACT</b></p><p>INTRODUCTION: Multiple Sclerosis (MS) is a chronic immune-mediated inflammatory disease (IMID) of the central nervous system (CNS). Early identification of MS, especially as a screening method for at-risk individuals, is crucial to delay disease progression and improve patient outcomes by preventing future irreversible neurologic damage. In this work, we utilize well-validated tracking scanning laser ophthalmoscope (TSLO) image to predict MS compared to the unaffected controls. While traditional Machine Learning (ML) methods, such as Logistic Regression (LR), have demonstrated a strong predictive power [Mauro F. Pinto et al., 2020] in disease identification, we propose the use of a novel DL based model. Though the use of Deep Neural Network (DNN), this model can have a much higher learning capacity to capture latent features embedded in the retinal images. We hypothesize that such latent information, often hidden in ML feature engineering processes, plays an important role for the prediction of disease and can be well represented by DL models.</p><p>OBJECTIVES: To establish a DL based model capable of learning latent image features to provide predictive power for the presence of MS.</p><p>AIMS: Utilize a deep convolutional neural network to extract the retinal coding and implement a recurrent neural network to learn the temporal correlations in video sequences.</p><p>METHODS: Our approaches were tested using a 250-subject MS/control database collected at the UCSF. Patients with Expanded Disability Status Scale (EDSS)< 4 are compared to healthy subjects. Both raw retinal images and the frequency and spatial patterns of the eye motion are combined to construct a hybrid image, denoted as \"retinal coding\", and directly fed to the DL model for training and testing.</p><p>RESULTS: Preliminary results on predictive power were measured using Area-under-Curve (AUC) of the Receiver Operating Characteristics (ROC) curve, sensitivity, and specificity, as well as an F-1 score. We observe an AUC of 0.920, sensitivity of 0.90, specificity of 0.89 and F-1 score of 0.89 using the DL model to distinguish MS from controls, which outperforms the baseline LR model by 24%.</p><p>CONCLUSIONS: This work can be considered as a proof-of-concept concerning the possibility of identifying MS disease using a DL based approach. The results demonstrate the possibility of predicting early-stage MS and understanding disease's dynamics. Such end-to-end model could be generalizable and trained on other disease states.</p><p>PMID:<a href=\"https://pubmed.ncbi.nlm.nih.gov/37733549/?utm_source=Other&utm_medium=rss&utm_campaign=pubmed-2&utm_content=10guX6I3SqrbUeeLKSTD6FCRM44ewnrN2MKKTQLLPMHB4xNsZU&fc=20210216052009&ff=20230921184032&v=2.17.9.post6+86293ac\">37733549</a> | DOI:<a href=\"https://doi.org/10.1167/jov.23.11.29\">10.1167/jov.23.11.29</a></p></div>", "link": "https://pubmed.ncbi.nlm.nih.gov/37733549/?fc=20210216052009&ff=20230921184032&v=2.17.9.post6+86293ac", "published_date": "2023-09-21T10:00:00Z", "source": "PubMed", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": false, "ml_prediction_lr": false, "discovery_date": "2023-09-21T22:40:34.308375Z", "noun_phrases": [ "Invited Session V", "The eye", "a window", "systemic and neurodegenerative health", "Early prediction", "multiple sclerosis", "laser ophthalmoscopy (SLO) video sequence data", "a Deep Learning (DL) based approach" ], "doi": "10.1167/jov.23.11.29", "access": "restricted", "takeaways": "Multiple Sclerosis (MS) is a chronic immune-mediated inflammatory disease of the central nervous system. Early identification of MS is crucial to delay disease progression and improve patient outcomes. In this work, we used a DL-based model to predict MS compared to unaffected controls. The model outperformed the baseline LR model by 24%.", "categories": [] }, { "article_id": 67440, "title": "Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis—a cross-sectional study", "summary": null, "link": "https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01247-z", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T21:33:05.371407Z", "noun_phrases": [ "PA", "sensorimotor capacity", "wearables", "multiple sclerosis" ], "doi": "10.1186/s12984-023-01247-z", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67439, "title": "Integrating single-nucleus sequence profiling to reveal the transcriptional dynamics of Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis", "summary": null, "link": "https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-023-04516-6", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T21:32:15.447006Z", "noun_phrases": [ "single-nucleus sequence profiling", "the transcriptional dynamics", "Alzheimer’s disease", "Parkinson’s disease", "multiple sclerosis" ], "doi": "10.1186/s12967-023-04516-6", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67297, "title": "Assessing walking ability using a robotic gait trainer: opportunities and limitations of assist-as-needed control in spinal cord injury", "summary": null, "link": "https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01226-4", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T19:32:55.282916Z", "noun_phrases": [ "walking ability", "a robotic gait trainer", "limitations", "assist-as-needed control", "spinal cord injury" ], "doi": "10.1186/s12984-023-01226-4", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67191, "title": "Retinal ganglion cell repopulation for vision restoration in optic neuropathy: a roadmap from the RReSTORe Consortium", "summary": null, "link": "https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-023-00655-y", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T17:33:06.239776Z", "noun_phrases": [ "Retinal ganglion cell repopulation", "vision restoration", "a roadmap", "the RReSTORe Consortium" ], "doi": "10.1186/s13024-023-00655-y", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67190, "title": "Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review", "summary": null, "link": "https://bmcsportsscimedrehabil.biomedcentral.com/articles/10.1186/s13102-023-00717-0", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T17:32:56.229541Z", "noun_phrases": [ "Measurement properties", "device-based physical activity instruments", "ambulatory adults", "physical disabilities", "chronic diseases", "a scoping review" ], "doi": "10.1186/s13102-023-00717-0", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67189, "title": "TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides", "summary": null, "link": "https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05463-1", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T17:32:26.429455Z", "noun_phrases": [ "TIPred", "a novel stacked ensemble approach", "the accelerated discovery", "tyrosinase inhibitory peptides" ], "doi": "10.1186/s12859-023-05463-1", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67188, "title": "Effectiveness of neuromuscular electrical stimulation in severe acute pancreatitis complicated patients with acute respiratory distress syndrome: study protocol for a randomized controlled trial", "summary": null, "link": "https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-023-07642-0", "published_date": "2023-09-20T23:00:00Z", "source": "BioMedCentral", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": null, "ml_prediction_lr": null, "discovery_date": "2023-09-21T17:32:16.254038Z", "noun_phrases": [ "Effectiveness", "neuromuscular electrical stimulation", "severe acute pancreatitis", "complicated patients", "acute respiratory distress syndrome", "study protocol", "a randomized controlled trial" ], "doi": "10.1186/s13063-023-07642-0", "access": "restricted", "takeaways": null, "categories": [] }, { "article_id": 67175, "title": "Intimate partner violence and multiple sclerosis", "summary": "<div><p>Mult Scler. 2023 Sep 21:13524585231197926. doi: 10.1177/13524585231197926. Online ahead of print.</p><p><b>ABSTRACT</b></p><p>People with MS may be at heightened risk of intimate partner violence (IPV) compared to the general population; however, little is known about the prevalence of IPV among people with MS or its effects on MS-specific clinical outcomes. Additionally, while MS clinicians often discuss family planning with patients, many clinicians may have received little training in detecting and responding to IPV. Moreover, no studies have investigated how to implement IPV case-finding and resource provision in the MS clinical setting. Overall, there are several scholarly, educational, and implementation-related gaps in IPV-associated care for people with MS. This article aims to summarize the available literature on IPV in people with MS, identify future research questions, and aid MS clinicians in safely addressing IPV while awaiting vital MS-specific knowledge.</p><p>PMID:<a href=\"https://pubmed.ncbi.nlm.nih.gov/37732567/?utm_source=Other&utm_medium=rss&utm_campaign=pubmed-2&utm_content=10guX6I3SqrbUeeLKSTD6FCRM44ewnrN2MKKTQLLPMHB4xNsZU&fc=20210216052009&ff=20230921130214&v=2.17.9.post6+86293ac\">37732567</a> | DOI:<a href=\"https://doi.org/10.1177/13524585231197926\">10.1177/13524585231197926</a></p></div>", "link": "https://pubmed.ncbi.nlm.nih.gov/37732567/?fc=20210216052009&ff=20230921130214&v=2.17.9.post6+86293ac", "published_date": "2023-09-21T10:00:00Z", "source": "PubMed", "publisher": null, "container_title": null, "authors": [], "relevant": null, "ml_prediction_gnb": false, "ml_prediction_lr": false, "discovery_date": "2023-09-21T17:02:18.705335Z", "noun_phrases": [ "Intimate partner violence", "multiple sclerosis" ], "doi": "10.1177/13524585231197926", "access": "restricted", "takeaways": "People with MS may be at a heightened risk of intimate partner violence compared to the general population. MS clinicians often discuss family planning with patients, but many have received little training in detecting and responding to IPV.", "categories": [] } ] }