Latest Articles for Patient Outcomes

HBP levels may predict bacterial infections in severe trauma cases.

Women face higher in-hospital mortality after CABG, especially over 60 years old.

This article explores how deep learning improves predictions in healthcare survival analysis.

A study reveals significant differences in TTS outcomes across racial and ethnic groups.

A new model predicts outcomes for ICU patients on mechanical ventilation.

Key elements affecting cancer return rates post-surgery are highlighted.

Study analyzes sedation levels for patients in ED versus ICU.

A new method improves causal inference in health research by combining diverse data sources.

A study examining how troponin levels relate to mortality in sepsis patients.

This study evaluates revision risks for various total hip implants across multiple registries.

Evaluating the effectiveness of EVT for stroke treatment with large-core infarcts.

CSA-Net improves segmentation accuracy for medical images, enhancing diagnostic capabilities.

AI tools improve glaucoma referrals and patient outcomes.

Research reveals potential therapies combining MLKL blocking and HHT for colorectal cancer.

New methods improve the efficiency and reliability of clinical trials.

Study reveals complex interactions between immune cells and diffuse large B-cell lymphoma.

A new method enhances healthcare predictions using external data sources.

Study links tumor growth rates to patient survival outcomes in cancer treatments.

Research explores machine learning models for predicting hospital mortality in hip fracture patients.

New methods enhance prediction accuracy and fairness in healthcare outcomes.

A joint model provides insights into cystic fibrosis patient outcomes and health events.

Investigating treatment effects and their variations among diverse populations using innovative approaches.

Higher EVT volumes in hospitals lead to better patient recovery rates.

Study highlights effects of chemotherapy on DNA changes and reproductive health.

Examining the difficulties in identifying extranodal extension and its impact on treatment.

A study reveals key causes of death among organ transplant patients.

Research explores how metabolism affects the success of CAR-T cell therapy for cancer.

This study enhances sepsis mortality predictions using effective machine learning techniques.

Examining patient survival with polyhazard models enhances data accuracy and treatment decisions.

New treatments show promise for advanced colorectal cancer patients.

Grotta bars provide detailed insights into stroke patient recovery outcomes.

This research explores T-cell behavior in multiple myeloma and its implications for treatment.

New research highlights how immune cells affect breast cancer patient outcomes.

Examining methods to enhance basket trials through information borrowing.

Examining methods for estimating treatment effects with missing data in electronic health records.

A study showcases a new model predicting sepsis-related deaths in hospitals.

A method to analyze patient treatment effects using existing data.

A method improving predictions in cancer treatment through image analysis.

New methods enhance evaluation of knee osteoarthritis severity for better outcomes.

A new method for analyzing survival data using functional approaches.