News
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Perspective on multi-modal modeling for biomarker discovery in oncology
Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalized medicine.
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Deep learning for monkeypox
The Gevaert lab spearheaded by visiting scholar Dr. Alexander Thieme has developed a model that is able to distinguish mpox skin lesions from other skin lesions.
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Imaging genomics: data fusion in uncovering disease heritability
Sequencing of the human genome in the early 2000s enabled probing of the genetic basis of disease on a scale previously unimaginable.
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AI based analysis of imaging, clinical & lab data to triage COVID19 patients.
We took advantage of a large cohort of Chinese PCR-confirmed COVID19 patients to embark on a biomedical data fusion project to triage COVID19 patients.
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Metalearning in oncology
RNA sequencing has emerged as a promising approach in cancer prognosis as RNA sequencing becomes more easily and affordable.