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Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Using Medical Text.
JMIR Med Inform
January 2025
Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China.
Background: Machine learning models can reduce the burden on doctors by converting medical records into International Classification of Diseases (ICD) codes in real time, thereby enhancing the efficiency of diagnosis and treatment. However, it faces challenges such as small datasets, diverse writing styles, unstructured records, and the need for semimanual preprocessing. Existing approaches, such as naive Bayes, Word2Vec, and convolutional neural networks, have limitations in handling missing values and understanding the context of medical texts, leading to a high error rate.
View Article and Find Full Text PDFPrimary intracranial extraosseous Ewing's sarcoma with intraspinal metastasis in children: illustrative case.
J Neurosurg Case Lessons
January 2025
Department of Neurosurgery, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Background: The diagnosis of intracranial extraosseous Ewing's sarcoma (EES) poses challenges due to the absence of specific clinical and imaging features prior to surgery. It is crucial to differentiate the tumor from other small round cell malignancies postoperatively.
Observations: A 7-year-old patient was admitted to the authors' hospital due to the in situ recurrence of a posterior fossa tumor more than 1 month after the initial surgery for headache.
The Utility of Cardiac Computed Tomographic Angiography in Differentiating Between Papillary Fibroelastoma, Infective Endocarditis, and Degeneration of the Aortic Valve.
J Comput Assist Tomogr
November 2024
From the Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD.
Purpose: Cardiac computed tomography angiography (CCTA) has significantly advanced the visualization of cardiac structures, particularly valves. We assessed the diagnostic performance of CCTA in diagnosing the most common disorders affecting the aortic valves requiring surgery-papillary fibroelastoma, infective endocarditis, and degeneration.
Methods: This retrospective study included patients who underwent aortic valve resection between 2016 and 2023 and had a preceding CCTA.
Use Of Patient Health Survey Data For Risk Adjustment To Limit Distortionary Coding Incentives In Medicare.
Health Aff (Millwood)
January 2025
Michael E. Chernew, Harvard University.
A core problem with the current risk-adjustment system in Medicare Advantage and accountable care organization (ACO) programs-the Hierarchical Condition Categories (HCC) model-is that the inputs (coded diagnoses) can be influenced for gain by risk-bearing plans or providers. Using existing survey data on health status (which provide less manipulable inputs), we found that the use of a hybrid risk score drawing from survey data and a scaled-back set of HCCs would, in addition to mitigating coding incentives, modestly lessen risk-selection incentives, strengthen payment incentives to deliver efficient care, allocate payment across ACOs more efficiently according to markers of population health that are not as affected by practice patterns or coding efforts, and redistribute payment in a manner that supports equity goals. Although sampling error and survey nonresponse present challenges, analyses suggest that these should not be prohibitive.
View Article and Find Full Text PDFBenchmark of Data Integration in Single-Cell Proteomics.
Anal Chem
January 2025
Zhejiang Provincial Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
Single-cell proteomics (SCP) detected based on different technologies always involves batch-specific variations because of differences in sample processing and other potential biases. How to integrate SCP data effectively has become a great challenge. Integration of SCP data not only requires the conservation of true biological variances, but also realizes the removal of unwanted batch effects.
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