Many patients with colorectal cancer (CRC) are diagnosed in the advanced stage, resulting in delayed treatment and reduced survival time. It is urgent to develop accurate early screening methods for CRC. The purpose of this study is to develop an art...
Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with the interpretability of linear models. ExplaiNN can predict TF b...
Cancer stem cells (CSCs), also known as tumor-initiating cells (TICs), are a subset of tumor cells that persist within tumors as a distinct population. They drive tumor initiation, relapse, and metastasis through self-renewal and differentiation into...
Current hardware limitations make it impossible to train convolutional neural networks on gigapixel image inputs directly. Recent developments in weakly supervised learning, such as attention-gated multiple instance learning, have shown promising res...
BACKGROUND: Electronic health records (EHRs) are generated at an ever-increasing rate. EHR trajectories, the temporal aspect of health records, facilitate predicting patients' future health-related risks. It enables healthcare systems to increase the...
Traffic Sign Recognition (TSR) is one of the many utilities made possible by embedded systems with internet connections. Through the usage of vehicular cameras, it's possible to capture and classify traffic signs in real time with Artificial Intellig...
Gait phase recognition is of great importance in the development of rehabilitation devices. The advantages of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) are combined (LSTM-CNN) in this paper, then a gait phase recognition me...
BACKGROUND: Unlike diseases, automatic recognition of disabilities has not received the same attention in the area of medical NLP. Progress in this direction is hampered by obstacles like the lack of annotated corpus. Neural architectures learn to tr...
Aerial imagery and video recordings of animals are used for many areas of research such as animal behaviour, behavioural neuroscience and field biology. Many automated methods are being developed to extract data from such high-resolution videos. Most...
PURPOSE: An end-to-end differentiable 2D Bloch simulation is used to reduce T induced blurring in single-shot turbo spin echo sequences, also called rapid imaging with refocused echoes (RARE) sequences, by using a joint optimization of refocusing fli...
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