Latest AI and machine learning research in critical care for healthcare professionals.
Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accurate risk stratification. However, existing machine learning models for sepsis prediction often suffer from poor interpretability, limited generalizability across diverse patient populations, and challenges in handling class imbalance and high-dimensional clinical data. To address these gaps, this s...
The extraction of visual features is an essential step in Visual Question Answering (VQA). Building a good visual representation of the analyzed scene is indeed one of the essential keys for the system to be able to correctly understand the latter in order to answer complex questions. In many fields such as remote sensing, the visual feature extraction step could benefit significantly from lever...
BACKGROUND: Long-term ventilator-dependent patients often face problems such as decreased quality of life, increased mortality, and increased medical ...
Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term...
Traumatic Brain Injury (TBI) is a major contributor to mortality among older adults, with geriatric patients facing disproportionately high risk due...
Respiratory viral infections pose a global health burden, yet the cellular immune responses driving protection or pathology remain unclear. Natural ...
Previous studies reported that opioids depress breathing by inhibiting respiratory neural networks in the brainstem. The effects of opioids on sensory...
The rapid advancement of Large Language Models (LLMs) has stimulated interest in multi-agent collaboration for addressing complex medical tasks. How...
The intensive care unit (ICU) manages critically ill patients, many of whom face a high risk of mortality. Early and accurate prediction of in-hospi...
This paper investigates approaches to enhance the reasoning capabilities of Large Language Model (LLM) agents using Reinforcement Learning (RL). Spe...
Single-source remote sensing object detection using optical or SAR images struggles in complex environments. Optical images offer rich textural deta...
Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patients' quality of life. This study aimed to establish...
While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly ...
Discussions about the benefits of admitting very old individuals to intensive care unit (ICU) remain challenging. We hypothesized that data-driven alg...
In 2019, Chi Mei Hospital built a private cloud AI service framework, incorporating HIS interface web service, data retrieval web service, and AI web ...
Explainable Artificial Intelligence (XAI) is crucial for enhancing transparency, interpretability and actionability of AI systems, particularly in hea...
This work aims to identify the Key Research Areas for building and deploying the semantic interoperability framework for the Intensive Medicine Data S...
The COVID-19 pandemic highlighted the complexities of diagnosing and managing acute Respiratory Failure (RF). Early prediction of RF remains a key cha...
Patients admitted to the intensive care unit (ICU) are often treated with multiple high-risk medications. Over- and underprescribing of indicated medi...
Artificial Intelligence (AI) has significantly advanced clinical decision support systems in healthcare, particularly using Machine Learning (ML) mode...