Hospital-Based Medicine

Current progress and future directions of intraoperative frozen section for spread through air spaces in lung cancer.

Spread through air spaces (STAS) is a recently recognized pattern of invasion in lung cancer that is strongly linked to postoperative recurrence and poor survival. For patients with early-stage disease eligible for sublobar resection, intraoperative identification of STAS on frozen section (FS) could theoretically inform surgical decision-making. However, accumulating evidence, including recent an...

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insuranc...

Plant Biofactories for Vaccination: Progress in Edible Vaccine Technologies as a Sustainable Approach to Global Immunization.

Globally, the pathogen-driven enteric diseases remain a leading cause of morbidity and mortality, disproportionately affecting populations in low-inco...

Prognostic value of preoperative CT-derived fractional flow reserve after transcatheter or surgical aortic valve replacement in patients with severe aortic stenosis.

BACKGROUND: Patients with aortic stenosis (AS) often have concomitant coronary artery disease (CAD), and coronary CTA (CCTA) is performed for anatomic...

Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.

BACKGROUND: Early prediction of hospital admission at the emergency department (ED) triage can improve patient flow and resource allocation. Most exis...

Predicting Psychiatric Readmission of Children and Adolescents Using Machine Learning.

INTRODUCTION: Recurrent psychiatric hospitalizations in youth are costly and burdensome to patients and families. While postdischarge planning rarely ...

Trigger tool methodologies in hospital settings: reappraising their role in pharmacovigilance and digital safety surveillance.

INTRODUCTION: Trigger tool methodologies have become important approaches for detecting adverse events in hospital care because they identify more har...

Perioperative corticosteroids and pancreatic surgery outcomes: a systematic review and meta-analysis combining human expertise and AI support (ChatGPT).

Pancreatic surgery is associated with high postoperative morbidity. The role of corticosteroids (CCS) in pancreatic surgery remains uncertain. Systema...

Impact of an Artificial Intelligence-Powered Clinical Decision Support System for Acute Kidney Injury Prevention in the Intensive Care Unit: Single-Center Uncontrolled Before-and-After Implementation Study.

BACKGROUND: Acute kidney injury (AKI) is a frequent and serious complication among hospitalized patients, particularly in critical care settings, wher...

Exploring the Potential of Ambient AI for Inpatient Documentation: A Qualitative Study with Junior Doctors.

Clinical documentation is essential for safe and effective patient care but places a substantial clerical burden on doctors, particularly those early ...

Gramado consensus on imaging evaluation of the response to neoadjuvant systemic therapy for breast cancer.

The assessment of response to neoadjuvant systemic therapy (NST) is a critical pillar in defining the multidisciplinary therapeutic strategy in breast...

Using machine learning to discriminate non-classical 21-hydroxylase deficiency from polycystic ovary syndrome: an external validation study.

INTRODUCTION: Nonclassical 21-hydroxylase deficiency (NC21OHD) is a rare autosomal recessive disorder that is frequently misdiagnosed as polycystic ov...

AI-based bone age assessment versus forensic expert panel: agreement, sex bias, and ethical implications.

BACKGROUND: Forensic age estimation is frequently requested when chronological age is unknown or contested. While automated bone age systems have been...

Feasibility of Tailoring Artificial Intelligence-Assisted Ambient Scribes for Intensive Care Unit Rounds: Algorithm Development and Validation.

BACKGROUND: The increasing documentation burden on physicians is a significant contributor to burnout and decreases in care quality. Artificial intell...

Evaluation of the Applicability of Synthetic Data in the Development of Colorectal Cancer Survival Prediction Models: External Validation of Advanced Machine Learning Models Based on National Cancer Data Center Data.

BACKGROUND: Limited data availability and privacy constraints hinder the development of robust survival prediction models for personalized treatment. ...

Hidden pathways of antimicrobial resistance: A review of environmental metagenomics and exposure risks in low-resource settings.

Antimicrobial resistance (AMR) is increasingly recognised as a One Health challenge in which environmental reservoirs play an important role in the pe...

Development of the CASPER-Score: A bedside tool integrating AI-based ECG analysis with key clinical predictors to identify relevant coronary artery stenosis in patients after out-of-hospital cardiac arrest.

INTRODUCTION: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality worldwide, frequently associated with acute coronary syndromes. Wh...

A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study.

BACKGROUND: Surgical treatment for spinal metastases is associated with high perioperative risk due to tumor burden, neurologic compromise, and limite...

A multicenter machine learning model for predicting ICU mortality in mechanically ventilated patients: development and external validation.

BACKGROUND: Accurate early prediction of mortality in mechanically ventilated intensive care unit (ICU) patients remains challenging due to disease he...

Development and multicenter validation of machine learning models for 28-day mortality in critically ill patients with acute exacerbation of chronic obstructive pulmonary disease.

BACKGROUND: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common critical illness in the intensive care unit (ICU) and is ...