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  Patient Subtyping via Time-Aware LSTM Networks

  • Published on: August, 2017
  • Xi Zhang, Anil K. Jain, Fei Wang, Jiayu Zhou, Cao Xiao, Inci M. Baytas
  • Code Available

  Grouping of patients based on similar disease progression pathways, also known as Patient Subtyping is extremely important to account heterogeneity in ...

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  Predicting the deterioration of COVID-19 patients in the emergency department

  • Published on: November, 2020
  • Yvonne W. Lui, David Kudlowitz, Taro Makino, Ben Zhang, Lea Azour, Carlos Fernandez-Granda, Siddhant Dogra, Yi...
  • Code Available

  During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decis ...

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  Multimodal Machine Learning-Based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

  • Published on: May, 2019
  • Stefan Klein, Esa Rahtu, Aleksei Tiulpin, Edwin H.G. Oei, Jer´ome Thevenot, Simo Saarakkala, Sita M.A. Bierma-...
  • Code Available

  This is a machine learning-based Knee osteoarthritis progression prediction model that utilizes radiographic data, clinical examination results and pr ...

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  A Machine Learning Approach to Predicting Readmission or Mortality in Patients Hospitalized for Stroke or Transient Ischemic Attack

  • Published on: September, 2020
  • Ling-Chien Hung, Sheng-Feng Sung and Ya-Han Hu
  • Code Available

  Stroke is one of the leading causes of adult disability and mortality worldwide. Stroke reoccurrence is predominant in survivors. Complications like p ...

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  Predicting survival of patients with heart failure from serum creatinine and ejection fraction alone using machine learning

  • Published on: February, 2020
  • Giuseppe Jurman , Davide Chicco
  • Code Available

  Heart failure is a common event in Cardiovascular Diseases(CVD). Early detection and proper management can be a great help to people with CVD. Model s ...

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  Temporal Phenotyping using Deep Predictive Clustering of Disease Progression

  • Published on: July, 2020
  • Changhee Lee, Mihaela van der Schaar
  • Code Available

  The model provides an actor-critic approach for temporal predictive clustering, AC-TPC, in which, a neural networks are used as an encoder, a selector ...

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  Explainable Prediction of Medical Codes from Clinical Text

  • Published on: December, 2019
  • James Mullenbach, Jimeng Sun, Sarah Wiegre?e, Jacob Eisenstein, Jon Duke
  • Code Available

  Clinical notes are typically accompanied by medical codes, which describe the diagnosis and treatment. Model is developed for automatic ICD code assig ...

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  Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer

  • Published on: January, 2020
  • Michael E. Draugelis, Mitesh S. Patel, Lawrence N. Shulman, Christopher Manz, Lynn M. Schuchter, Susan Harknes...
  • Code Available

  Patients with cancer that are at risk of short-term mortality could be identified using machine learning algorithms. It is unclear how different machi ...

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  Machine learning techniques for personalized breast cancer risk prediction

  • Published on: April, 2020
  • Chang Ming, Ivo Dinov
  • Code Available

  Breast cancer risk prediction modeling allows researchers to identify high-risk patients and reduce unnecessary interventions. Currently, breast cance ...

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  Inter-Series Attention Model for COVID-19 Forecasting

  • Published on: October, 2020
  • Yu-Xiang Wang, Xifeng Yan , Xiaoyong Jin
  • Code Available

  The Coronavirus disease 2019 (COVID-19) has been impacting the human society since early 2020. During this public health crisis, reliable forecasting ...