Region-specific Diffeomorphic Metric Mapping

NeurIPS 2019 1 code implementation

We explore a family of RDMM registration approaches: 1) a registration model where regions with separate regularizations are pre-defined (e. g., in an atlas space or for distinct foreground and background regions), 2) a registration model where a general spatially-varying regularizer is estimated, and 3) a registration model where the spatially-varying regularizer is obtained via an end-to-end trained deep learning (DL) model.

IMAGE REGISTRATION

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts

7 Nov 20161 code implementation

Objective: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain.

ACTIVE LEARNING

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

24 Jan 20191 code implementation

Nevertheless, a main impediment for the adoption of Deep Learning in healthcare is its reduced interpretability, for in this field it is crucial to gain insight on the why of predictions, to assure that models are actually learning relevant features instead of spurious correlations.

MORTALITY PREDICTION

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

27 Jan 20201 code implementation

In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.

CHATBOT MACHINE READING COMPREHENSION QUESTION ANSWERING QUESTION GENERATION

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