Product Alert

Latest AI and machine learning research in product alert for healthcare professionals.

12,617 articles
Stay Ahead - Weekly Product Alert research updates
Subscribe
Browse Categories
Showing 1741-1760 of 12,617 articles

From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development

Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During the development of new drugs, clinical trials are used not only to evaluate the safety and efficacy of the drug but also to explore its dosage, treatment regimens, and potential side effects. This review discusses the various stages of clinical trial...

Concept Bottleneck Large Language Models

We introduce Concept Bottleneck Large Language Models (CB-LLMs), a novel framework for building inherently interpretable Large Language Models (LLMs). In contrast to traditional black-box LLMs that rely on limited post-hoc interpretations, CB-LLMs integrate intrinsic interpretability directly into the LLMs -- allowing accurate explanations with scalability and transparency. We build CB-LLMs for ...

Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to...

Test-time Correction with Human Feedback: An Online 3D Detection System via Visual Prompting

This paper introduces Test-time Correction (TTC) system, a novel online 3D detection system designated for online correction of test-time errors via...

A Pipeline and NIR-Enhanced Dataset for Parking Lot Segmentation

Discussions of minimum parking requirement policies often include maps of parking lots, which are time consuming to construct manually. Open source ...

Take Fake as Real: Realistic-like Robust Black-box Adversarial Attack to Evade AIGC Detection

The security of AI-generated content (AIGC) detection is crucial for ensuring multimedia content credibility. To enhance detector security, research...

Event fields: Capturing light fields at high speed, resolution, and dynamic range

Event cameras, which feature pixels that independently respond to changes in brightness, are becoming increasingly popular in high-speed application...

Post-hoc Probabilistic Vision-Language Models

Vision-language models (VLMs), such as CLIP and SigLIP, have found remarkable success in classification, retrieval, and generative tasks. For this, ...

Quantum Threat in Healthcare IoT: Challenges and Mitigation Strategies

The Internet of Things (IoT) has transformed healthcare, facilitating remote patient monitoring, enhanced medication adherence, and chronic disease ...

Multiclass Post-Earthquake Building Assessment Integrating Optical and SAR Satellite Imagery, Ground Motion, and Soil Data with Transformers

Timely and accurate assessments of building damage are crucial for effective response and recovery in the aftermath of earthquakes. Conventional pre...

Benchmarking Attention Mechanisms and Consistency Regularization Semi-Supervised Learning for Post-Flood Building Damage Assessment in Satellite Images

Post-flood building damage assessment is critical for rapid response and post-disaster reconstruction planning. Current research fails to consider t...

OMENN: One Matrix to Explain Neural Networks

Deep Learning (DL) models are often black boxes, making their decision-making processes difficult to interpret. This lack of transparency has driven...

Quantifying the Reliability of Predictions in Detection Transformers: Object-Level Calibration and Image-Level Uncertainty

DEtection TRansformer (DETR) has emerged as a promising architecture for object detection, offering an end-to-end prediction pipeline. In practice, ...

TinyFusion: Diffusion Transformers Learned Shallow

Diffusion Transformers have demonstrated remarkable capabilities in image generation but often come with excessive parameterization, resulting in co...

Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement

Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting ti...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of ...

Nov 22 2024 39575788
Deep operator network models for predicting post-burn contraction

Burn injuries present a significant global health challenge. Among the most severe long-term consequences are contractures, which can lead to functi...

Mitigating Matching Biases Through Score Calibration

Record matching, the task of identifying records that correspond to the same real-world entities across databases, is critical for data integration ...

Toward a responsible future: recommendations for AI-enabled clinical decision support.

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challeng...

Nov 1 2024 39325508
Facing Identity: The Formation and Performance of Identity via Face-Based Artificial Intelligence Technologies

How is identity constructed and performed in the digital via face-based artificial intelligence technologies? While questions of identity on the tex...

Browse Categories