AIMC Topic: Retrospective Studies

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[Effectiveness of robot assisted percutaneous kyphoplasty for treatment of single/double-segment osteoporotic vertebral compression fractures].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
OBJECTIVE: To compare the effectiveness of robot assisted and C-arm assisted percutaneous kyphoplasty (PKP) in the treatment of single/double-segment osteoporotic vertebral compression fracture (OVCF).

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

European heart journal
AIMS: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-en...

Deep Learning for Automated Diabetic Retinopathy Screening Fused With Heterogeneous Data From EHRs Can Lead to Earlier Referral Decisions.

Translational vision science & technology
PURPOSE: Fundus images are typically used as the sole training input for automated diabetic retinopathy (DR) classification. In this study, we considered several well-known DR risk factors and attempted to improve the accuracy of DR screening.

Automatic detection of oral cancer in smartphone-based images using deep learning for early diagnosis.

Journal of biomedical optics
SIGNIFICANCE: Oral cancer is a quite common global health issue. Early diagnosis of cancerous and potentially malignant disorders in the oral cavity would significantly increase the survival rate of oral cancer. Previously reported smartphone-based i...

Predictive Risk Models for Wound Infection-Related Hospitalization or ED Visits in Home Health Care Using Machine-Learning Algorithms.

Advances in skin & wound care
OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate descriptio...

Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.

Anesthesia and analgesia
BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk factors have been previously identified, no methods currently exist to determin...

Deep-Learning-Based Diagnosis of Bedside Chest X-ray in Intensive Care and Emergency Medicine.

Investigative radiology
OBJECTIVES: Validation of deep learning models should separately consider bedside chest radiographs (CXRs) as they are the most challenging to interpret, while at the same time the resulting diagnoses are important for managing critically ill patient...

A Simulated Prospective Evaluation of a Deep Learning Model for Real-Time Prediction of Clinical Deterioration Among Ward Patients.

Critical care medicine
OBJECTIVES: The National Early Warning Score, Modified Early Warning Score, and quick Sepsis-related Organ Failure Assessment can predict clinical deterioration. These scores exhibit only moderate performance and are often evaluated using aggregated ...