Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records

Suicide is a leading cause of death in the US, particularly for young people, veterans and Native Americans. An early warning system can be an effective way to identify those in need before a crisis is upon them. See how AI and machine learning on longitudinal health records can be used to identify those at risk – up to 60+ times as likely to attempt a suicide in a future 1 year period.

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Pazopanib or methotrexate-vinblastine combination chemotherapy in adult patients with progressive desmoid tumours (DESMOPAZ): a non-comparative, randomised, open-label, multicentre, phase 2 study.

BACKGROUND: Desmoid tumours are locally aggressive tumours associated with substantial morbidity. No systemic treatments are approved for this disease, with methotrexate-vinblastine the only chemotherapy regimen assessed in a clinical trial setting to date. VEGF overexpression is a common feature in aggressive desmoid tumours.

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Translation and evaluation of a pre-clinical 5-protein response prediction signature in a breast cancer phase Ib clinical trial.

Human protein biomarker discovery relies heavily on pre-clinical models, in particular established cell lines and patient-derived xenografts, but confirmation studies in primary tissue are essential to demonstrate clinical relevance. We describe in this study the process that was followed to clinically translate a 5-protein response signature predictive for the activity of an anti-HER3 monoclonal

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Data-independent acquisition mass spectrometry to quantify protein levels in FFPE tumor biopsies for molecular diagnostics.

Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay.

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Characterization of MGMT and EGFR protein expression in glioblastoma and association with survival.

PURPOSE: Understanding the molecular landscape of glioblastoma (GBM) is increasingly important in the age of targeted therapy. O-6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation and EGFR amplification are markers that may play a role in prognostication, treatment, and/or clinical trial eligibility. Quantification of MGMT and EGFR protein expression may offer an alternative stra

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Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine

Lung cancer is the leading cause of cancer death worldwide. Early detection of individuals at risk of lung cancer is critical to reduce the mortality rate. Using data from individual patient electronic health records (EHR’s), we retrospectively developed and prospectively validated an accurate risk prediction model of new incident lung cancer occurring in the next 1 year. Through statistical lear

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Targeted multiplex proteomics for molecular prescreening and biomarker discovery in metastatic colorectal cancer.

Protein biomarkers are widely used in cancer diagnosis, prognosis, and prediction of treatment response. Here we introduce the use of targeted multiplex proteomics (TMP) as a tool to simultaneously measure a panel of 54 proteins involved in oncogenic, tumour suppression, drug metabolism and resistance, in patients with metastatic colorectal cancer (mCRC). TMP provided valuable diagnostic informati

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A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data

The rapid deterioration observed in the condition of some hospitalized patients can be attributed to either disease progression or imperfect triage and level of care assignment after their admission. In this study, data collected from a system-wide electronic medical record (EMR) were exposed to multiple machine learning methods. The prospectively validated algorithm scored patients’ daily and lon

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