Care of terminally ill / Palliative care

End-to-End Deep Learning for Interior Tomography with Low-Dose X-ray CT

Objective: There exist several X-ray computed tomography (CT) scanning strategies to reduce a radiation dose, such as (1) sparse-view CT, (2) low-dose CT, and (3) region-of-interest (ROI) CT (called interior tomography). To further reduce the dose, the sparse-view and/or low-dose CT settings can be applied together with interior tomography. Interior tomography has various advantages in terms of ...

Perception-as-Control: Fine-grained Controllable Image Animation with 3D-aware Motion Representation

Motion-controllable image animation is a fundamental task with a wide range of potential applications. Recent works have made progress in controlling camera or object motion via various motion representations, while they still struggle to support collaborative camera and object motion control with adaptive control granularity. To this end, we introduce 3D-aware motion representation and propose ...

A Trust-Guided Approach to MR Image Reconstruction with Side Information

Reducing MRI scan times can improve patient care and lower healthcare costs. Many acceleration methods are designed to reconstruct diagnostic-qualit...

LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating

An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience...

GIT-CXR: End-to-End Transformer for Chest X-Ray Report Generation

Medical imaging is crucial for diagnosing, monitoring, and treating medical conditions. The medical reports of radiology images are the primary medi...

Attribute-Based Robotic Grasping with Data-Efficient Adaptation

Robotic grasping is one of the most fundamental robotic manipulation tasks and has been the subject of extensive research. However, swiftly teaching...

Predicting dry matter intake in cattle at scale using gradient boosting regression techniques and Gaussian process boosting regression with Shapley additive explanation explainable artificial intelligence, MLflow, and its containerization.

Dry matter intake (DMI) is a measure critical to managing and evaluating livestock. Methods exist for quantifying individual DMI in dry lot settings t...

UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery

Unmanned aerial vehicle object detection (UAV-OD) has been widely used in various scenarios. However, most existing UAV-OD algorithms rely on manual...

Single-and double-strand circulating DNA fragmentomics for enhanced cancer detection performance

In early detection of cancer, the use of circulating cell-free DNA (cirDNA) obtained from blood samples is notable for its minimally invasive nature. ...

BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML

Large language model (LLM) agents hold promise for accelerating biomedical research and development (R&D). Several biomedical agents have recently bee...

PyCLM: programming-free, closed-loop microscopy for real-time measurement, segmentation, and optogenetic stimulation

In cell biology, optical techniques are increasingly used to measure cells’ internal states (biosensors) and to stimulate cellular responses (optogene...

JAX Animal Behavior System (JABS): A genetics informed, end-to-end advanced behavioral phenotyping platform for the laboratory mouse

Automated detection of complex animal behavior remains a challenge in neuroscience. Developments in computer vision have greatly advanced automated be...

Frequency-Aware Interpretable Deep Learning Framework for Alzheimer’s Disease Classification Using rs-fMRI

Gaining insight into the spectral and temporal alterations in brain connectivity associated with Alzheimer’s disease (AD) may offer pathways toward mo...

Pathologist-interpretable breast cancer subtyping and stratification from AI-inferred nuclear features

Artificial intelligence (AI) is making notable advances in digital pathology but faces challenges in human interpretability. Here we introduce EXPAND ...

RawBench: A Comprehensive Benchmarking Framework for Raw Nanopore Signal Analysis Techniques

Nanopore sequencing technologies continue to advance rapidly, offering critical benefits such as real-time analysis, the ability to sequence extremely...

Accurate and efficient phylogenetic inference through end-to-end deep learning

Accurate phylogenetic inference is crucial for understanding evolutionary relationships among species. Deep learning technique has been introduced for...

One-Class Bioacoustic Detector for Monitoring the Critically Endangered Pied Tamarin (Saguinus bicolor)

The pied tamarin (Saguinus bicolor) is a critically endangered primate with a small geographic range that includes fragmented urban forest mosaics in ...

Deciphering the Antigenic Evolution of Seasonal Influenza A Viruses with PREDAC-Transformer: From Antigenic Clustering to Key Site Identification

Seasonal influenza viruses undergo continuous antigenic drift due to mutations in the hemagglutinin (HA) protein, rendering vaccines ineffective and p...

PRSNet-2: End-to-end genotype-to-phenotype prediction via hierarchical graph neural networks

The emergence of large-scale biobanks has opened unprecedented opportunities for the development of data-driven approaches, especially deep learning-b...

Direct Training of Networks of Morris-Lecar Neurons with Backprop

Spiking Neural Networks (SNNs) have the potential to replicate the brain’s computational efficacy by explicitly incorporating action potentials or “sp...