AIMC Topic: Humans

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Interpretability-Guided Inductive Bias For Deep Learning Based Medical Image.

Medical image analysis
Deep learning methods provide state of the art performance for supervised learning based medical image analysis. However it is essential that trained models extract clinically relevant features for downstream tasks as, otherwise, shortcut learning an...

Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence.

Journal of biomedical informatics
BACKGROUND: A patient's health information is generally fragmented across silos because it follows how care is delivered: multiple providers in multiple settings. Though it is technically feasible to reunite data for analysis in a manner that underpi...

Development and validation of a meta-learning-based multi-modal deep learning algorithm for detection of peritoneal metastasis.

International journal of computer assisted radiology and surgery
PURPOSE: The existing medical imaging tools have a detection accuracy of 97% for peritoneal metastasis(PM) bigger than 0.5 cm, but only 29% for that smaller than 0.5 cm, the early detection of PM is still a difficult problem. This study is aiming at ...

Collaborative Control Method and Experimental Research on Robot-Assisted Craniomaxillofacial Osteotomy Based on the Force Feedback and Optical Navigation.

The Journal of craniofacial surgery
OBJECTIVE: Surgical robot has advantages in high accuracy and stability. But during the robot-assisted bone surgery, the lack of force information from surgical area and incapability of intervention from surgeons become the obstacle. The aim of the s...

Patient safety classifications, taxonomies and ontologies: A systematic review on development and evaluation methodologies.

Journal of biomedical informatics
INTRODUCTION: Patient safety classifications/ontologies enable patient safety information systems to receive and analyze patient safety data to improve patient safety. Patient safety classifications/ontologies have been developed and evaluated using ...

"Note Bloat" impacts deep learning-based NLP models for clinical prediction tasks.

Journal of biomedical informatics
One unintended consequence of the Electronic Health Records (EHR) implementation is the overuse of content-importing technology, such as copy-and-paste, that creates "bloated" notes containing large amounts of textual redundancy. Despite the rising i...

DeepBindBC: A practical deep learning method for identifying native-like protein-ligand complexes in virtual screening.

Methods (San Diego, Calif.)
Identifying native-like protein-ligand complexes (PLCs) from an abundance of docking decoys is critical for large-scale virtual drug screening in early-stage drug discovery lead searching efforts. Providing reliable prediction is still a challenge fo...

Comparison of perioperative outcomes following transperitoneal versus retroperitoneal robot-assisted partial nephrectomy: a propensity-matched analysis of VCQI database.

World journal of urology
OBJECTIVE: To compare perioperative outcomes following retroperitoneal robot-assisted partial nephrectomy (RPRAPN) and transperitoneal robot-assisted partial nephrectomy (TPRAPN).