BACKGROUND Accurate data on the prognosis of bone metastases are necessary for appropriate treatment.Immune checkpoint inhibitors(ICIs)are widely used in the treatment of gene mutation-negative non-small cell lung can...BACKGROUND Accurate data on the prognosis of bone metastases are necessary for appropriate treatment.Immune checkpoint inhibitors(ICIs)are widely used in the treatment of gene mutation-negative non-small cell lung cancer(GMN-NSCLC).AIM To investigate the prognostic factors in patients with bone metastases from GMNNSCLC following ICI use.METHODS This retrospective cohort study included 45 patients with GMN-NSCLC who were treated for bone metastases from 2017 to 2022 and received chemotherapy after diagnosis.Using Kaplan–Meier curves and Cox proportional hazards models,we evaluated the association between overall survival(OS)and clinical parameters,including serum biochemical concentrations and blood cell count.RESULTS Univariate analysis showed that Eastern Cooperative Oncology Group performance status≤1 and the use of ICIs and bone-modifying agents after bone metastasis diagnosis were significantly associated with a favorable OS.Multivariate analysis revealed that ICI use after bone metastasis diagnosis was signicantly associated with a favorable OS.CONCLUSION ICI use after bone metastasis diagnosis may be a favorable prognostic factor in patients with bone metastases of GMN-NSCLC.Consideration of ICI treatment for bone metastasis and GMN-NSCLC is warranted to establish a more accurate predictive nomogram for patients with bone metastasis.展开更多
In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthca...In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.展开更多
文摘BACKGROUND Accurate data on the prognosis of bone metastases are necessary for appropriate treatment.Immune checkpoint inhibitors(ICIs)are widely used in the treatment of gene mutation-negative non-small cell lung cancer(GMN-NSCLC).AIM To investigate the prognostic factors in patients with bone metastases from GMNNSCLC following ICI use.METHODS This retrospective cohort study included 45 patients with GMN-NSCLC who were treated for bone metastases from 2017 to 2022 and received chemotherapy after diagnosis.Using Kaplan–Meier curves and Cox proportional hazards models,we evaluated the association between overall survival(OS)and clinical parameters,including serum biochemical concentrations and blood cell count.RESULTS Univariate analysis showed that Eastern Cooperative Oncology Group performance status≤1 and the use of ICIs and bone-modifying agents after bone metastasis diagnosis were significantly associated with a favorable OS.Multivariate analysis revealed that ICI use after bone metastasis diagnosis was signicantly associated with a favorable OS.CONCLUSION ICI use after bone metastasis diagnosis may be a favorable prognostic factor in patients with bone metastases of GMN-NSCLC.Consideration of ICI treatment for bone metastasis and GMN-NSCLC is warranted to establish a more accurate predictive nomogram for patients with bone metastasis.
基金funded by Stefan cel Mare University of Suceava,Romania.
文摘In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.
