Medical Ethics / Professional Responsibility

Image quality improvement of single-shot turbo spin-echo magnetic resonance imaging of female pelvis using a convolutional neural network.

We have developed a deep learning-based approach to improve image quality of single-shot turbo spin-...

A critical perspective on guidelines for responsible and trustworthy artificial intelligence.

Artificial intelligence (AI) is among the fastest developing areas of advanced technology in medicin...

DNN-Dom: predicting protein domain boundary from sequence alone by deep neural network.

MOTIVATION: Accurate delineation of protein domain boundary plays an important role for protein engi...

Investigation of Low-Dose CT Lung Cancer Screening Scan "Over-Range" Issue Using Machine Learning Methods.

Low-dose computed tomography (CT) lung cancer screening is recommended by the US Preventive Services...

Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers.

Clinical text de-identification enables collaborative research while protecting patient privacy and ...

Recurrent Deep Network Models for Clinical NLP Tasks: Use Case with Sentence Boundary Disambiguation.

Although a number of foundational natural language processing (NLP) tasks like text segmentation are...

ConDo: protein domain boundary prediction using coevolutionary information.

MOTIVATION: Domain boundary prediction is one of the most important problems in the study of protein...

Skeletal bone age assessments for young children based on regression convolutional neural networks.

Pediatricians and pediatric endocrinologists utilize Bone Age Assessment (BAA) for in-vestigations p...

Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aid...

Towards Data-Driven Autonomous Robot-Assisted Physical Rehabilitation Therapy.

Task-oriented therapy consists of three stages: demonstration, observation and assistance. While dem...

DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional LSTM.

Protein domain boundary prediction is usually an early step to understand protein function and struc...

Automatic Organ Segmentation for CT Scans Based on Super-Pixel and Convolutional Neural Networks.

Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial t...

A Fully Convolutional Deep Neural Network for Lung Tumor Boundary Tracking in MRI.

Delineation of lung tumor from adjacent tissue from a series of magnetic resonance images (MRI) pose...

Fetal MRI Synthesis via Balanced Auto-Encoder Based Generative Adversarial Networks.

Machine learning approaches for image analysis require large amounts of training imaging data. As an...

De-identification of patient notes with recurrent neural networks.

OBJECTIVE: Patient notes in electronic health records (EHRs) may contain critical information for me...

Boundary-Pushing Healthcare Tech.

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration.

PURPOSE: In an attempt to overcome several hurdles that exist in organ segmentation approaches, the ...

Medical image segmentation via atlases and fuzzy object models: Improving efficacy through optimum object search and fewer models.

PURPOSE: Statistical object shape models (SOSMs), known as probabilistic atlases, are popular in med...

Thinking science with thinking machines: The multiple realities of basic and applied knowledge in a research border zone.

Some scholars dismiss the distinction between basic and applied science as passé, yet substantive as...

Classification of imbalanced bioinformatics data by using boundary movement-based ELM.

To address the imbalanced classification problem emerging in Bioinformatics, a boundary movement-bas...

A Frequency-based Strategy of Obtaining Sentences from Clinical Data Repository for Crowdsourcing.

In clinical NLP, one major barrier to adopting crowdsourcing for NLP annotation is the issue of conf...