AIMC Topic: Prognosis

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Incorporating medical code descriptions for diagnosis prediction in healthcare.

BMC medical informatics and decision making
BACKGROUND: Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches m...

Predicting cognitive behavioral therapy outcome in the outpatient sector based on clinical routine data: A machine learning approach.

Behaviour research and therapy
The availability of large-scale datasets and sophisticated machine learning tools enables developing models that predict treatment outcomes for individual patients. However, few studies used routinely available sociodemographic and clinical data for ...

Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to com...

Analysis of disease comorbidity patterns in a large-scale China population.

BMC medical genomics
BACKGROUND: Disease comorbidity is popular and has significant indications for disease progress and management. We aim to detect the general disease comorbidity patterns in Chinese populations using a large-scale clinical data set.

Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges.

Cancer letters
Cancer is an aggressive disease with a low median survival rate. Ironically, the treatment process is long and very costly due to its high recurrence and mortality rates. Accurate early diagnosis and prognosis prediction of cancer are essential to en...

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

JAMA network open
IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and r...

Analysis of Decision Tree and K-Nearest Neighbor Algorithm in the Classification of Breast Cancer.

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: The death rate of breast tumour is falling as there is progress in its research area. However, it is the most common disease among women. It is a great challenge in designing a machine learning model to evaluate the performance of the clas...

Usefulness of presepsin as diagnostic and prognostic marker of sepsis in daily clinical practice.

Journal of infection in developing countries
INTRODUCTION: Sepsis represents a major cause of morbidity and mortality in critically ill patients. Early diagnosis and appropriate treatment have a crucial influence on survival. The aim of this study was to evaluate the diagnostic and prognostic r...