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TranscriptomicsChromosomal copy number aberrations in colorectal metastases resemble their primary counterparts and differences are typically non-recurrent.
Background & Aims: The metastatic process is complex and remains a major obstacle in the management of colorectal cancer (CRC). To gain a better insight into the biologic events driving the metastatic process we investigated genomic aberrations in a large cohort of matched CRC primaries and distant ...
ORGANISM(S): Homo sapiens 
2014-02-10 | E-GEOD-38479 | biostudies-arrayexpress
UnknownTreatment of Uterine Fibroid–Related Heavy Menstrual Bleeding: Variations in Clinical Practice at Four Hospitals in the Netherlands
Not available
S-EPMC12936386 | biostudies-literature
UnknownEffectiveness and safety of tofacitinib for ulcerative colitis: two-year results of the ICC Registry.
Not available
S-EPMC10092078 | biostudies-literature
UnknownAnemia and Iron Deficiency in Outpatients with Inflammatory Bowel Disease: Ubiquitous Yet Suboptimally Managed.
Not available
S-EPMC9692778 | biostudies-literature
TranscriptomicsBeyond KRAS mutation status: influence of KRAS copy number status and microRNAs on response to cetuximab in metastatic colorectal cancer patients
KRAS mutation is a negative predictive factor for treatment with anti-epidermal growth factor receptor (EGFR) antibodies in metastatic colorectal cancer (mCRC). Novel predictive markers are required to further improve the selection of patients for this treatment. Here, we assessed the influence of m...
ORGANISM(S): Homo sapiens 
2012-01-01 | E-GEOD-32048 | biostudies-arrayexpress
UnknownPredictors for extubation failure in COVID-19 patients using a machine learning approach.
Not available
S-EPMC8711075 | biostudies-literature
UnknownRisk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.
Not available
S-EPMC8236316 | biostudies-literature
UnknownSome Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.
Not available
S-EPMC8522869 | biostudies-literature
UnknownPredicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.
Not available
S-EPMC9583049 | biostudies-literature
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