Prescriptions

Universally Designed Augmented Reality as Interface for Artificial Intelligence Assisted Decision-Making in Everyday Life Scenarios.

This paper presents a conceptual prototype that integrates Artificial Intelligence (AI) and Augmented Reality (AR) with the principles of Universal Design (UD) to enhance decision-making in everyday scenarios for a diverse user base, eliminating the need for conventional text or voice AI interfaces. The study employed a mixed-method approach, including surveys, user testing, and interviews with ei...

PickScan: Object discovery and reconstruction from handheld interactions

Reconstructing compositional 3D representations of scenes, where each object is represented with its own 3D model, is a highly desirable capability in robotics and augmented reality. However, most existing methods rely heavily on strong appearance priors for object discovery, therefore only working on those classes of objects on which the method has been trained, or do not allow for object manip...

Artificial Intelligence Chatbots in Patient Communication: Current Possibilities.

ChatGPT, an artificial intelligence (AI) chatbot, can generate text prompts based on user input. This study investigated the possibility of utilizing ...

WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking

While deep learning has revolutionized computer-aided drug discovery, the AI community has predominantly focused on model innovation and placed less...

Language-Model Prior Overcomes Cold-Start Items

The growth of recommender systems (RecSys) is driven by digitization and the need for personalized content in areas such as e-commerce and video str...

A Quality-Centric Framework for Generic Deepfake Detection

Detecting AI-generated images, particularly deepfakes, has become increasingly crucial, with the primary challenge being the generalization to previ...

Error-controlled Progressive Retrieval of Scientific Data under Derivable Quantities of Interest

The unprecedented amount of scientific data has introduced heavy pressure on the current data storage and transmission systems. Progressive compress...

Equivariant Graph Attention Networks with Structural Motifs for Predicting Cell Line-Specific Synergistic Drug Combinations

Cancer is the second leading cause of death, with chemotherapy as one of the primary forms of treatment. As a result, researchers are turning to dru...

Simulation of Nanorobots with Artificial Intelligence and Reinforcement Learning for Advanced Cancer Cell Detection and Tracking

Nanorobots are a promising development in targeted drug delivery and the treatment of neurological disorders, with potential for crossing the blood-...

Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction

Subgraph-based methods have proven to be effective and interpretable in predicting drug-drug interactions (DDIs), which are essential for medical pr...

Differentiable Physics-based System Identification for Robotic Manipulation of Elastoplastic Materials

Robotic manipulation of volumetric elastoplastic deformable materials, from foods such as dough to construction materials like clay, is in its infan...

CACER: Clinical concept Annotations for Cancer Events and Relations.

OBJECTIVE: Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescrip...

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development.

Despite increasing interest in using Artificial Intelligence (AI) and Machine Learning (ML) models for drug development, effectively interpreting thei...

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This study explores the potential use of ChatGPT, an AI-based language model, in assessing herbal-drug interactions (HDi) to enhance clinical decision...

Implementation and Application of an Intelligibility Protocol for Interaction with an LLM

Our interest is in constructing interactive systems involving a human-expert interacting with a machine learning engine on data analysis tasks. This...

Domain Specific Data Distillation and Multi-modal Embedding Generation

The challenge of creating domain-centric embeddings arises from the abundance of unstructured data and the scarcity of domain-specific structured da...

FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference

Personalized Federated Graph Learning (pFGL) facilitates the decentralized training of Graph Neural Networks (GNNs) without compromising privacy whi...

Simultaneously Infer Cell Pseudotime,Velocity Field and Gene Interaction from Multi-Branch scRNA-seq Data with scPN

Modeling cellular dynamics from single-cell RNA sequencing (scRNA-seq) data is critical for understanding cell development and underlying gene regul...

DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis

Existing graph learning-based cognitive diagnosis (CD) methods have made relatively good results, but their student, exercise, and concept represent...

ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design

Engineering molecules to exhibit precise 3D intermolecular interactions with their environment forms the basis of chemical design. In ligand-based d...