Published in Informatics in Medicine Unlocked
• State-of-the-art review on emerging machine learning techniques for diagnosing COVID-19 from routine laboratory and clinical data. • Proposed an ensemble learning model for initial screening of COVID-19 patients from routine blood tests. • Achieved high accuracy of 99.88% in distinguishing COVID-19 positive cases from normal ones. • ERLX model pr...
Published in BMC Medical Informatics and Decision Making
BackgroundThe recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests.MethodsIn this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine lear...
Published in Cancer immunology, immunotherapy : CII
The immune microenvironment plays a vital role in the progression of hepatocellular carcinoma (HCC). Thousands of immune-related genes (IRGs) have been identified, but their effects on HCC are not fully understood. In this study, we identified the differentially expressed IRGs and analyzed their functions in HCC in a systematic way. Furthermore, we...
Published in Neurobiology of disease
Medulloblastoma is the most common malignant pediatric brain tumor with high fatality rate. Recent large-scale studies utilizing genome-wide technologies have sub-grouped medulloblastomas into four major subgroups: wingless (WNT), sonic hedgehog (SHH), group 3, and group 4. However, there has yet to be a global analysis of long non-coding RNAs, a c...
Published in The Journal of infection
Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The modified T-SPOT.TB assay was performed in 499 participants (243 ATB and 256 LTBI) and another 322 participants (162 ATB and 160 LTBI) who were diagnosed in Qiaokou (training) and Caidian (validation) cohort respectively. The mean spot ...
Published in Open Physics
In this study the low visibility in Nanjing city is classified and predicted using observed data during 2014 to 2016 with machine-learning based decision tree algorithm (4.5). For this purpose, the model was trained with 3/4th of the data samples until the self-learning accuracy of the model reached 88.32%. The remaining 1/4th of the data samples w...
Published in World journal of urology
Selecting patients for intensified treatment for upper tract urothelial carcinoma can be challenging, partly due to the lack of accurate preoperative staging tools. Several preoperative staging models for upper tract urothelial carcinoma have been presented, but none have been externally validated. The aim of the current study was to perform an ext...
Published in Saudi Journal of Biological Sciences
In order to assess the efficacy of 18F-FDG PET/CT-based diagnostic model in diagnosing colorectal cancer (CRC) lymph node metastasis (LNM), the 18F-FDG PET/CT medical records of CRC patients were acquired, and the CRC regional LNM diagnostic model was constructed through the combination of image and grain factors of 18F-FDG PET/CT. The specific ana...
Published in BMC Gastroenterology
BackgroundsTo investigate the value of prolactin (PRL) in diagnosing non-alcoholic fatty liver disease (NAFLD).MethodsMetabolic parameters and serum PRL levels were measured in 452 males and 421 females, who were randomized to the estimation or the validation group as a 1:1 ratio. Hepatic steatosis was diagnosed via abdominal ultrasound. Variables ...
Published in Respiratory Research
BackgroundThe differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In recent years, artificial intelligence (AI) machine learning algorithms have started being used to an increasing extent in disease diagnosis due to the high level of efficiency, objectivity, and accuracy that they offer.MethodsData samples on 192 patients w...
