| scholarly article | Q13442814 |
| P50 | author | Randall K Ten Haken | Q50795388 |
| Issam El Naqa | Q57612481 | ||
| Feng-Ming Spring Kong | Q85174881 | ||
| P2093 | author name string | Yi Luo | |
| Dipankar Ray | |||
| Theodore S Lawrence | |||
| Dawn Owen | |||
| Shruti Jolly | |||
| Daniel L McShan | |||
| Martha M Matuszak | |||
| Ines Lohse | |||
| P2860 | cites work | MicroRNAs, TGF-β signaling, and the inflammatory microenvironment in cancer | Q26777313 |
| Genetic variation in the TGF-β signaling pathway and colon and rectal cancer risk | Q30498922 | ||
| Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. | Q31050064 | ||
| Stratification bias in low signal microarray studies | Q33296342 | ||
| Analysis of clinical and dosimetric factors associated with severe acute radiation pneumonitis in patients with locally advanced non-small cell lung cancer treated with concurrent chemotherapy and intensity-modulated radiotherapy | Q33907268 | ||
| Morbidity related to axillary irradiation in the treatment of breast cancer | Q34033298 | ||
| Nondosimetric risk factors for radiation-induced lung toxicity. | Q35456001 | ||
| Prediction of radiation pneumonitis by dose - volume histogram parameters in lung cancer--a systematic review | Q35757052 | ||
| Interference with transforming growth factor-beta/ Smad3 signaling results in accelerated healing of wounds in previously irradiated skin | Q35843231 | ||
| TGF-beta 1 inhibition of IFN-gamma-induced signaling and Th1 gene expression in CD4+ T cells is Smad3 independent but MAP kinase dependent | Q36259774 | ||
| Interleukin (IL) 15 is a novel cytokine that activates human natural killer cells via components of the IL-2 receptor | Q36363861 | ||
| The biology of interleukin-2 and interleukin-15: implications for cancer therapy and vaccine design | Q36547207 | ||
| Receiver operating characteristic analysis: a tool for the quantitative evaluation of observer performance and imaging systems | Q36782038 | ||
| Cytokines in radiobiological responses: a review | Q37045283 | ||
| Predictive markers of radiation pneumonitis. | Q37254071 | ||
| Ipsilateral lung dose volume parameters predict radiation pneumonitis in addition to classical dose volume parameters in locally advanced NSCLC treated with combined modality therapy | Q37653975 | ||
| Radiation oncology in the era of precision medicine. | Q38786662 | ||
| Cytokine production of lung cancer cell lines: Correlation between their production and the inflammatory/immunological responses both in vivo and in vitro | Q40131006 | ||
| IFN-gamma abrogates profibrogenic TGF-beta signaling in liver by targeting expression of inhibitory and receptor Smads | Q40204600 | ||
| Cellular basis of radiation-induced fibrosis | Q40418343 | ||
| Bayesian network ensemble as a multivariate strategy to predict radiation pneumonitis risk | Q40934956 | ||
| HITON: a novel Markov Blanket algorithm for optimal variable selection. | Q42110804 | ||
| Suggestion for a new grading scale for radiation induced pneumonitis based on radiological findings of computerized tomography: correlation with clinical and radiotherapeutic parameters in lung cancer patients | Q46582560 | ||
| Factors predicting radiation pneumonitis in lung cancer patients: a retrospective study | Q47757232 | ||
| Radiation-induced lung damage – Clinical risk profiles and predictive imaging on their way to risk-adapted individualized treatment planning? | Q64030456 | ||
| Evaluation of two dose-volume histogram reduction models for the prediction of radiation pneumonitis | Q77358019 | ||
| A prospective study on radiation pneumonitis following conformal radiation therapy in non-small-cell lung cancer: clinical and dosimetric factors analysis | Q79996337 | ||
| Association of DNA repair and steroid metabolism gene polymorphisms with clinical late toxicity in patients treated with conformal radiotherapy for prostate cancer | Q83201821 | ||
| P433 | issue | 1 | |
| P921 | main subject | Bayesian network | Q812540 |
| P304 | page(s) | 85-92 | |
| P577 | publication date | 2017-02-22 | |
| P1433 | published in | Radiotherapy and Oncology | Q14251029 |
| P1476 | title | Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis | |
| P478 | volume | 123 |
| Q64929608 | A multiobjective Bayesian networks approach for joint prediction of tumor local control and radiation pneumonitis in nonsmall-cell lung cancer (NSCLC) for response-adapted radiotherapy. |
| Q92494753 | Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage |
| Q47442495 | Deep reinforcement learning for automated radiation adaptation in lung cancer. |
| Q92258300 | Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer |
| Q47681393 | Discovery and application of immune biomarkers for hematological malignancies. |
| Q59793835 | Feature selection for the accurate prediction of septic and cardiogenic shock ICU mortality in the acute phase |
| Q55428338 | Machine Learning and Radiogenomics: Lessons Learned and Future Directions. |
| Q57167662 | Machine learning and modeling: Data, validation, communication challenges |
| Q57785736 | Radiation Therapy Outcomes Models in the Era of Radiomics and Radiogenomics: Uncertainties and Validation |
| Q47924326 | Radiation-induced lung toxicity in non-small-cell lung cancer: Understanding the interactions of clinical factors and cytokines with the dose-toxicity relationship |
| Q38665620 | Radiogenomics and radiotherapy response modeling. |
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