The Experts below are selected from a list of 208923 Experts worldwide ranked by ideXlab platform
Jacob C. Easaw - One of the best experts on this subject based on the ideXlab platform.
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P17.56A 3-Dimensional Matrix ASSAY TO HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: UPDATE OF RESULTS AND SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:INTRODUCTION: Usual treatment for glioblastoma is surgical resection, if possible, followed by radiotherapy with adjuvant chemotherapy using temozolomide. However a significant number of patients have a short response to temozolomide and subsequently a poorer prognosis. We investigated the possibility that surgical specimens obtained at the time of surgery might provide valuable information regarding sensitivity to chemotherapies, including temozolomide. In order to do this we used a 3-Dimensional Matrix assay that mimics brain. We analyzed a subgroup of these patients for O-6-methylguanine-DNA methyltransferase (MGMT) status and correlated this with the response of tumor tissue in the assay to temozolomide. METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSION: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor.
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A 3-Dimensional Matrix ASSAY THAT MAY HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:BACKGROUND: (blind field). METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSIONS: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor. SECONDARY CATEGORY: n/a.
Guillaume Lecué - One of the best experts on this subject based on the ideXlab platform.
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Sharp oracle inequalities for the prediction of a high-Dimensional Matrix
2017Co-Authors: Stéphane Gaïffas, Guillaume LecuéAbstract:We observe $(X_i,Y_i)_{i=1}^n$ where the $Y_i$'s are real valued outputs and the $X_i$'s are $m\times T$ matrices. We observe a new entry $X$ and we want to predict the output $Y$ associated with it. We focus on the high-Dimensional setting, where $m T \gg n$. This includes the Matrix completion problem with noise, as well as other problems. We consider linear prediction procedures based on different penalizations, involving a mixture of several norms: the nuclear norm, the Frobenius norm and the $\ell_1$-norm. For these procedures, we prove sharp oracle inequalities, using a statistical learning theory point of view. A surprising fact in our results is that the rates of convergence do not depend on $m$ and $T$ directly. The analysis is conducted without the usually considered incoherency condition on the unknown Matrix or restricted isometry condition on the sampling operator. Moreover, our results are the first to give for this problem an analysis of penalization (such nuclear norm penalization) as a regularization algorithm: our oracle inequalities prove that these procedures have a prediction accuracy close to the deterministic oracle one, given that the reguralization parameters are well-chosen.
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Sharp oracle inequalities for high-Dimensional Matrix prediction.
IEEE Transactions on Information Theory, 2017Co-Authors: Stéphane Gaïffas, Guillaume LecuéAbstract:We observe $(X_i,Y_i)_{i=1}^n$ where the $Y_i$'s are real valued outputs and the $X_i$'s are $m\times T$ matrices. We observe a new entry $X$ and we want to predict the output $Y$ associated with it. We focus on the high-Dimensional setting, where $m T \gg n$. This includes the Matrix completion problem with noise, as well as other problems. We consider linear prediction procedures based on different penalizations, involving a mixture of several norms: the nuclear norm, the Frobenius norm and the $\ell_1$-norm. For these procedures, we prove sharp oracle inequalities, using a statistical learning theory point of view. A surprising fact in our results is that the rates of convergence do not depend on $m$ and $T$ directly. The analysis is conducted without the usually considered incoherency condition on the unknown Matrix or restricted isometry condition on the sampling operator. Moreover, our results are the first to give for this problem an analysis of penalization (such nuclear norm penalization) as a regularization algorithm: our oracle inequalities prove that these procedures have a prediction accuracy close to the deterministic oracle one, given that the reguralization parameters are well-chosen.
Joseph F. Megyesi - One of the best experts on this subject based on the ideXlab platform.
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P17.56A 3-Dimensional Matrix ASSAY TO HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: UPDATE OF RESULTS AND SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:INTRODUCTION: Usual treatment for glioblastoma is surgical resection, if possible, followed by radiotherapy with adjuvant chemotherapy using temozolomide. However a significant number of patients have a short response to temozolomide and subsequently a poorer prognosis. We investigated the possibility that surgical specimens obtained at the time of surgery might provide valuable information regarding sensitivity to chemotherapies, including temozolomide. In order to do this we used a 3-Dimensional Matrix assay that mimics brain. We analyzed a subgroup of these patients for O-6-methylguanine-DNA methyltransferase (MGMT) status and correlated this with the response of tumor tissue in the assay to temozolomide. METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSION: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor.
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A 3-Dimensional Matrix ASSAY THAT MAY HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:BACKGROUND: (blind field). METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSIONS: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor. SECONDARY CATEGORY: n/a.
Stéphane Gaïffas - One of the best experts on this subject based on the ideXlab platform.
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Sharp oracle inequalities for the prediction of a high-Dimensional Matrix
2017Co-Authors: Stéphane Gaïffas, Guillaume LecuéAbstract:We observe $(X_i,Y_i)_{i=1}^n$ where the $Y_i$'s are real valued outputs and the $X_i$'s are $m\times T$ matrices. We observe a new entry $X$ and we want to predict the output $Y$ associated with it. We focus on the high-Dimensional setting, where $m T \gg n$. This includes the Matrix completion problem with noise, as well as other problems. We consider linear prediction procedures based on different penalizations, involving a mixture of several norms: the nuclear norm, the Frobenius norm and the $\ell_1$-norm. For these procedures, we prove sharp oracle inequalities, using a statistical learning theory point of view. A surprising fact in our results is that the rates of convergence do not depend on $m$ and $T$ directly. The analysis is conducted without the usually considered incoherency condition on the unknown Matrix or restricted isometry condition on the sampling operator. Moreover, our results are the first to give for this problem an analysis of penalization (such nuclear norm penalization) as a regularization algorithm: our oracle inequalities prove that these procedures have a prediction accuracy close to the deterministic oracle one, given that the reguralization parameters are well-chosen.
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Sharp oracle inequalities for high-Dimensional Matrix prediction.
IEEE Transactions on Information Theory, 2017Co-Authors: Stéphane Gaïffas, Guillaume LecuéAbstract:We observe $(X_i,Y_i)_{i=1}^n$ where the $Y_i$'s are real valued outputs and the $X_i$'s are $m\times T$ matrices. We observe a new entry $X$ and we want to predict the output $Y$ associated with it. We focus on the high-Dimensional setting, where $m T \gg n$. This includes the Matrix completion problem with noise, as well as other problems. We consider linear prediction procedures based on different penalizations, involving a mixture of several norms: the nuclear norm, the Frobenius norm and the $\ell_1$-norm. For these procedures, we prove sharp oracle inequalities, using a statistical learning theory point of view. A surprising fact in our results is that the rates of convergence do not depend on $m$ and $T$ directly. The analysis is conducted without the usually considered incoherency condition on the unknown Matrix or restricted isometry condition on the sampling operator. Moreover, our results are the first to give for this problem an analysis of penalization (such nuclear norm penalization) as a regularization algorithm: our oracle inequalities prove that these procedures have a prediction accuracy close to the deterministic oracle one, given that the reguralization parameters are well-chosen.
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High Dimensional Matrix estimation with unknown variance of the noise
Statistica Sinica, 2017Co-Authors: Olga Klopp, Stéphane GaïffasAbstract:We propose a new pivotal method for estimating high-Dimensional matrices. Assume that we observe a small set of entries or linear combinations of entries of an unknown Matrix $A_0$ corrupted by noise. We propose a new method for estimating $A_0$ which does not rely on the knowledge or an estimation of the standard deviation of the noise $\sigma$. Our estimator achieves, up to a logarithmic factor, optimal rates of convergence under the Frobenius risk and, thus, has the same prediction performance as previously proposed estimators which rely on the knowledge of $\sigma$. Our method is based on the solution of a convex optimization problem which makes it computationally attractive.
Penny Costello - One of the best experts on this subject based on the ideXlab platform.
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P17.56A 3-Dimensional Matrix ASSAY TO HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: UPDATE OF RESULTS AND SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:INTRODUCTION: Usual treatment for glioblastoma is surgical resection, if possible, followed by radiotherapy with adjuvant chemotherapy using temozolomide. However a significant number of patients have a short response to temozolomide and subsequently a poorer prognosis. We investigated the possibility that surgical specimens obtained at the time of surgery might provide valuable information regarding sensitivity to chemotherapies, including temozolomide. In order to do this we used a 3-Dimensional Matrix assay that mimics brain. We analyzed a subgroup of these patients for O-6-methylguanine-DNA methyltransferase (MGMT) status and correlated this with the response of tumor tissue in the assay to temozolomide. METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSION: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor.
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A 3-Dimensional Matrix ASSAY THAT MAY HELP PREDICT TREATMENT RESPONSE TO TEMOZOLOMIDE IN PATIENTS WITH GLIOBASTOMA: SUBGROUP ANALYSIS OF PATIENTS UNDERGOING MGMT TESTING
Neuro-Oncology, 2014Co-Authors: Joseph F. Megyesi, Penny Costello, Warren Mcdonald, David R. Macdonald, Jacob C. EasawAbstract:BACKGROUND: (blind field). METHODS: Records for patients treated for newly diagnosed or recurrent glioblastoma were analyzed. All patients had undergone surgical resection and tumor specimens at time of surgery were available for culture in a 3-Dimensional Matrix assay and observed for growth and invasion. Drug effects on mean invasion and growth were expressed as a ratio relative to control conditions. Length of survival was compared between temozolomide treated patients whose screening results had predicted a positive or negative response to temozolomide. The MGMT status of a subgroup of these patients was analyzed and correlated with the response of tumor tissue in the assay to temozolomide. RESULTS: Fifty-eight patients with glioblastoma were assessed. Each patient's tumor displayed a unique invasion and response profile. We looked in particular at the correlation between the outcome of a patient with glioblastoma treated with temozolomide and the response of that patient's tumor tissue to temozolomide in the 3-Dimensional assay. Mean survival time for patients whose tumors were not significantly sensitive to temozolomide in the assay was 181.7 +/- 43 days. Mean survival time for patients whose tumors were significantly sensitive to temozolomide in the assay was 290.0 +/- 33 days. Twelve patients underwent MGMT testing. In 10 of the 12 patients there was a correlation between tumor response in the assay and MGMT status. CONCLUSIONS: The 3-Dimensional assay may help predict glioblastoma patients who will show a treatment response to temozolomide. There appears to be a positive correlation between the response profiles in the assay to the MGMT status of the patient's tumor. SECONDARY CATEGORY: n/a.