Head Trauma

Identification and Validation of Liver Transplantation-Induced Acute Lung Injury Biomarkers Using a Bioinformatics and Experimental Approach.

BACKGROUND Acute lung injury (ALI) after liver transplantation (LT) is a critical complication negatively affecting transplant outcomes and patient survival. However, effective biomarkers for early diagnosis remain unidentified. This study aimed to identify hub biomarkers and signaling pathways involved in post-LT ALI through integrated bioinformatics and machine-learning analyses and to validate ...

Approach to Optimizing Tranexamic Acid Use in Trauma: Potential Utilization of Trauma Phenotypes.

Tranexamic acid (TXA) reduces mortality in patients with trauma; however, optimal patient selection remains unclear. This study aimed to identify trauma subgroups most likely to benefit from TXA administration by integrating systematic evidence mapping with trauma phenotype analysis derived from the Japan Trauma Data Bank.We conducted a two-phase study: first, a systematic search of MEDLINE, Web o...

A Machine Learning-Based Prognostic Model for Sepsis-Associated Liver Injury Using Routine Indicators.

OBJECTIVE: Sepsis-associated liver injury (SALI) occurs in approximately 40% of sepsis cases and is linked to high mortality, a challenge that may ste...

Neuroprognostication via Radiomics and Machine Learning Following Neonatal Hypoxic-Ischemic Insult.

OBJECTIVE: To produce objective predictions of neurodevelopmental outcomes after perinatal hypoxic-ischemic insult for the full spectrum of severity o...

Research on the Application Value of Blood Plasma Autofluorescence Spectroscopy Model Constructed by Machine Learning Algorithms in Identifying the Types of Post-operative Kidney Transplantation Injury.

BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...

Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often results in hyperdensities on non-contrast CT (NCCT...

Enhancing dental clinical education through AI: insights into post-clinical summaries.

BACKGROUND: Artificial Intelligence (AI) is increasingly being introduced into clinical education, including dentistry, as a supplement to traditional...

Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study.

BACKGROUND: Hematoma expansion or rebleeding after decompressive craniectomy (DC) is a critical determinant of poor prognosis in traumatic brain injur...

Predicting health-related quality of life two years post-diagnosis across seven cancer types: using machine learning to identify vulnerable patients.

PURPOSE: Cancer survivors often experience long-term consequences affecting their Health-Related Quality of Life (HRQoL). Sociodemographic factors, cl...

Mechanistic signatures of comorbid PTSD with cognitive impairment implicate cortisol-induced neural toxicity.

The men and women who worked in rescue and recovery operations at the 9/11 World Trade Center site are developing cognitive impairment (CI) at mid-lif...

Recognizing EEG responses to active TMS vs. sham stimulations in different TMS-EEG datasets: A machine learning approach.

Transcranial Magnetic Stimulation with simultaneous Electroencephalogram (TMS-EEG) allows for the assessment of neurophysiological properties of corti...

Commercially Available Artificial Intelligence Score on Preoperative Mammography for Prediction of Future Breast Cancer After DCIS Treatment.

Background: Mammographic artificial intelligence (AI) systems have been explored for future breast cancer risk prediction. Objective: To investigate a...

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study.

BACKGROUND: Self-reported, computerized history taking (CHT) may enable efficient collection of medical histories for acute chest pain management. OBJ...

The human metabolome and machine learning improves predictions of the post-mortem interval.

An accurate prediction of the time since death, known as the post-mortem interval, remains a critical research question in forensic and police investi...

Rethinking multivariate modeling in long-term forecasting: an efficient univariate framework with power decomposition and post-Calibration.

Long-term time series forecasting (LTSF) is critical to industrial applications. While recent advances mainly focus on modeling complex multivariate i...

Periodontal bone loss analysis via keypoint detection with heuristic post-processing.

OBJECTIVES: This study proposes a deep learning framework and an annotation methodology for the automatic detection of periodontal bone loss landmarks...

Artificial intelligence-driven predictive analytics for postoperative management and recovery in trauma patients.

PURPOSE OF REVIEW: Post-traumatic care is evolving from a reactive, protocol-driven paradigm to a predictive, personalized approach. This review exami...

Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?

Kidney transplantation is usually the optimal treatment option for patients living with kidney failure given its associations with improved survival, ...

Early Prediction of Adverse Stroke Outcomes using Non-clinical Factors and Missing Data: A Machine Learning Study.

Introduction Early prediction of stroke outcomes using prognostic tools may help clinical decision making and inform resource allocation. However, cli...

Readability, Accuracy, and Lexical Diversity of New ChatGPT Models for Common Carpal Tunnel Syndrome Questions.

BACKGROUND: Carpal tunnel syndrome (CTS) is a prevalent neuropathy in hand surgery that significantly affects people's quality of life. Frequently, pa...