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    Shanghai Jiao Tong University School of Medicine Reports Findings in Non-Small C ell Lung Cancer (Machine learning reveals CAT gene as a novel potential diagnost ic and prognostic biomarker in nonsmall cell lung cancer)

    48-49页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Non-Small C ell Lung Cancer is the subject of a report.According to news reporting originat ing from Shanghai, People’s Republic of China, by NewsRx correspondents,researc h stated, “Non-small cell lung cancer (NSCLC) represents one of the most prevale ntforms of lung cancer, with a five-year survival rate of 21.7%. T here is an urgent need to identify pertinentbiomarkers to inform the diagnosis and prognosis of tumors, particularly those that can be applied todifferent age groups.”

    Shanghai Jiao Tong University School of Medicine Reports Findings in Non-Small C ell Lung Cancer (Machine learning reveals CAT gene as a novel potential diagnost ic and prognostic biomarker in nonsmall cell lung cancer)

    48-49页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Non-Small C ell Lung Cancer is the subject of a report.According to news reporting originat ing from Shanghai, People’s Republic of China, by NewsRx correspondents,researc h stated, “Non-small cell lung cancer (NSCLC) represents one of the most prevale ntforms of lung cancer, with a five-year survival rate of 21.7%. T here is an urgent need to identify pertinentbiomarkers to inform the diagnosis and prognosis of tumors, particularly those that can be applied todifferent age groups.”

    Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medic ine Reports Findings in Breast Cancer (Novel models by machine learning to predi ct the risk of cardiac disease-specific death in young patients with breast canc er)

    50-51页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Breast Canc er is the subject of a report. Accordingto news reporting originating in Shangh ai, People’s Republic of China, by NewsRx journalists, researchstated, “With th e tremendous leap of various adjuvant therapies, breast cancer (BC)-related deat hs havedecreased significantly. Increasing attention was focused on the effect of cardiac disease on BC survivors,while limited existing population-based stud ies lay emphasis on the young age population.”

    Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medic ine Reports Findings in Breast Cancer (Novel models by machine learning to predi ct the risk of cardiac disease-specific death in young patients with breast canc er)

    50-51页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Breast Canc er is the subject of a report. Accordingto news reporting originating in Shangh ai, People’s Republic of China, by NewsRx journalists, researchstated, “With th e tremendous leap of various adjuvant therapies, breast cancer (BC)-related deat hs havedecreased significantly. Increasing attention was focused on the effect of cardiac disease on BC survivors,while limited existing population-based stud ies lay emphasis on the young age population.”

    Research Conducted at Pacific Northwest National Laboratory Has Provided New Inf ormation about Machine Learning (Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model Yolo)

    51-52页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in Machine Learning. According to news originatingfrom Richland, Washington, by Ne wsRx correspondents, research stated, “Streambed grain sizes controlriver hydro -biogeochemical (HBGC) processes and functions. However, measuring their quantit ies,distributions, and uncertainties is challenging due to the diversity and he terogeneity of natural streams.”Funders for this research include Biological and Environmental Research, United States Department ofEnergy (DOE), Battelle Memorial Institute.

    Research Conducted at Pacific Northwest National Laboratory Has Provided New Inf ormation about Machine Learning (Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model Yolo)

    51-52页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in Machine Learning. According to news originatingfrom Richland, Washington, by Ne wsRx correspondents, research stated, “Streambed grain sizes controlriver hydro -biogeochemical (HBGC) processes and functions. However, measuring their quantit ies,distributions, and uncertainties is challenging due to the diversity and he terogeneity of natural streams.”Funders for this research include Biological and Environmental Research, United States Department ofEnergy (DOE), Battelle Memorial Institute.

    Liaoning University Reports Findings in Machine Learning (Labyrinthine Wrinkle-P atterned Fiber Sensors Based on a 3D Stress Complementary Strategy for Machine L earning-Enabled Medical Monitoring and Action Recognition)

    52-53页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Machine Learning is the subject o f a report. According to news reportingoriginating from Liaoning, People’s Repu blic of China, by NewsRx correspondents, research stated, “Fiberstrain sensors show good application potential in the field of wearable smart fabrics and equip ment becauseof their characteristics of easy deformation and weaving. However, the integration of fiber strain sensorswith sensitive response, good stretchabi lity, and effective practical application remains a challenge.”Funders for this research include National Natural Science Foundation of China, Natural Science Foundationof Liaoning Province.

    Liaoning University Reports Findings in Machine Learning (Labyrinthine Wrinkle-P atterned Fiber Sensors Based on a 3D Stress Complementary Strategy for Machine L earning-Enabled Medical Monitoring and Action Recognition)

    52-53页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - New research on Machine Learning is the subject o f a report. According to news reportingoriginating from Liaoning, People’s Repu blic of China, by NewsRx correspondents, research stated, “Fiberstrain sensors show good application potential in the field of wearable smart fabrics and equip ment becauseof their characteristics of easy deformation and weaving. However, the integration of fiber strain sensorswith sensitive response, good stretchabi lity, and effective practical application remains a challenge.”Funders for this research include National Natural Science Foundation of China, Natural Science Foundationof Liaoning Province.

    New Data from Tomas Bata University Zlin Illuminate Findings in Nanofibers (Adso rption Capacity Prediction and Optimization of Electrospun Nanofiber Membranes f or Estrogenic Hormone Removal Using Machine Learning Algorithms)

    53-54页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Fresh data on Nanotechnology - Nanofibers are pre sented in a new report. According to newsreporting originating from Zlin, Czech Republic, by NewsRx correspondents, research stated, “This studyfocuses on dev eloping four machine learning (ML) models (Gaussian process regression (GPR), su pportvector machine (SVM), decision tree (DT), and ensemble learning tree (ELT) ) optimized and hyperparameterstuned via genetic algorithm (GA) and particle sw arm optimization (PSO) to analyze and predictthe adsorption capacity of four es trogenic hormones. These hormones are a serious cause of fish femininityand var ious forms of cancer in humans.”

    New Data from Tomas Bata University Zlin Illuminate Findings in Nanofibers (Adso rption Capacity Prediction and Optimization of Electrospun Nanofiber Membranes f or Estrogenic Hormone Removal Using Machine Learning Algorithms)

    53-54页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Fresh data on Nanotechnology - Nanofibers are pre sented in a new report. According to newsreporting originating from Zlin, Czech Republic, by NewsRx correspondents, research stated, “This studyfocuses on dev eloping four machine learning (ML) models (Gaussian process regression (GPR), su pportvector machine (SVM), decision tree (DT), and ensemble learning tree (ELT) ) optimized and hyperparameterstuned via genetic algorithm (GA) and particle sw arm optimization (PSO) to analyze and predictthe adsorption capacity of four es trogenic hormones. These hormones are a serious cause of fish femininityand var ious forms of cancer in humans.”