Pneumonia

LLM-RG4: Flexible and Factual Radiology Report Generation across Diverse Input Contexts

Drafting radiology reports is a complex task requiring flexibility, where radiologists tail content to available information and particular clinical demands. However, most current radiology report generation (RRG) models are constrained to a fixed task paradigm, such as predicting the full ``finding'' section from a single image, inherently involving a mismatch between inputs and outputs. The tr...

Multilabel Classification for Lung Disease Detection: Integrating Deep Learning and Natural Language Processing

Classifying chest radiographs is a time-consuming and challenging task, even for experienced radiologists. This provides an area for improvement due to the difficulty in precisely distinguishing between conditions such as pleural effusion, pneumothorax, and pneumonia. We propose a novel transfer learning model for multi-label lung disease classification, utilizing the CheXpert dataset with over ...

Deep Learning-Based Noninvasive Screening of Type 2 Diabetes with Chest X-ray Images and Electronic Health Records

The imperative for early detection of type 2 diabetes mellitus (T2DM) is challenged by its asymptomatic onset and dependence on suboptimal clinical ...

Generative AI: A Pix2pix-GAN-Based Machine Learning Approach for Robust and Efficient Lung Segmentation

Chest radiography is climacteric in identifying different pulmonary diseases, yet radiologist workload and inefficiency can lead to misdiagnoses. Au...

CareBot: A Pioneering Full-Process Open-Source Medical Language Model

Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. Howeve...

CoinCLIP: A Multimodal Framework for Assessing Viability in Web3 Memecoins

The rapid growth of memecoins within the Web3 ecosystem, driven by platforms like Pump.fun, has made it easier for anyone to create tokens. However,...

Contextualized Counterspeech: Strategies for Adaptation, Personalization, and Evaluation

AI-generated counterspeech offers a promising and scalable strategy to curb online toxicity through direct replies that promote civil discourse. How...

CAD-Unet: A Capsule Network-Enhanced Unet Architecture for Accurate Segmentation of COVID-19 Lung Infections from CT Images

Since the outbreak of the COVID-19 pandemic in 2019, medical imaging has emerged as a primary modality for diagnosing COVID-19 pneumonia. In clinica...

Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora

The BabyLM Challenge is a community effort to close the data-efficiency gap between human and computational language learners. Participants compete ...

Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation

Radiology report generation (RRG) has shown great potential in assisting radiologists by automating the labor-intensive task of report writing. Whil...

DiffSign: AI-Assisted Generation of Customizable Sign Language Videos With Enhanced Realism

The proliferation of several streaming services in recent years has now made it possible for a diverse audience across the world to view the same me...

MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting

In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new...

Harnessing Multiple Correlated Networks for Exact Community Recovery

We study the problem of learning latent community structure from multiple correlated networks, focusing on edge-correlated stochastic block models w...

Hierarchical feature extraction on functional brain networks for autism spectrum disorder identification with resting-state fMRI data

Autism Spectrum Disorder (ASD) is a pervasive developmental disorder of the central nervous system, primarily manifesting in childhood. It is charac...

Deep Neural Network-Based Prediction of B-Cell Epitopes for SARS-CoV and SARS-CoV-2: Enhancing Vaccine Design through Machine Learning

The accurate prediction of B-cell epitopes is critical for guiding vaccine development against infectious diseases, including SARS and COVID-19. Thi...

Libra: Leveraging Temporal Images for Biomedical Radiology Analysis

Radiology report generation (RRG) requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. While multim...

Agent-Based Modelling Meets Generative AI in Social Network Simulations

Agent-Based Modelling (ABM) has emerged as an essential tool for simulating social networks, encompassing diverse phenomena such as information diss...

ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation

AI-driven models have demonstrated significant potential in automating radiology report generation for chest X-rays. However, there is no standardiz...

Suspected Undeclared Use of Artificial Intelligence in the Academic Literature: An Analysis of the Academ-AI Dataset

Since generative artificial intelligence (AI) tools such as OpenAI's ChatGPT became widely available, researchers have used them in the writing proc...

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...