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您的检索式：作者名="Muhammad Tayyeb"
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| 1 | Autoimmune diabetes from pembrolizumab:A case report and review of literature显示文摘BACKGROUND Immunotherapy,specifically the use of checkpoint inhibitors such as pembrolizumab,has become an important tool in personalized cancer therapy.These inhibitors target proteins on T-cells that regulate the immune response against tumor cells.Pembrolizumab,which targets the programmed cell death 1 receptor on T-cells,has been approved for the treatment of metastatic melanoma and nonsmall cell lung cancer.However,it can also lead to immune-related side effects,including pneumonitis,colitis,thyroid abnormalities,and rare cases of type 1 diabetes.CASE SUMMARY The case presented involves an adult patient in 30s with breast cancer who developed hyperglycemia after receiving pembrolizumab treatment.The patient was diagnosed with diabetic ketoacidosis and further investigations were performed to evaluate for new-onset type 1 diabetes.The patient had a history of hypothyroidism and a family history of breast cancer.Treatment for diabetic ketoacidosis was initiated,and the patient was discharged for close follow-up with an endocrinologist.CONCLUSION This literature review highlights the occurrence of diabetic ketoacidosis and newonset type 1 diabetes in patients receiving pembrolizumab treatment for different types of cancer.Overall,the article emphasizes the therapeutic benefits of immunotherapy in cancer treatment,particularly pembrolizumab,while also highlighting the potential side effect of immune-related diabetes that can occur in a small percentage of patients.Here we present a case where pembrolizumab lead to development of diabetes after a few cycles highlighting one of the rare yet a serious toxicity of the drug. | Hardikkumar Bhanderi Farhan Khalid Zubair Hassan Bodla Tayyeb Muhammad Doantrang Du Trishala Meghal | 2023 | World Journal of Clinical Oncology2023，14，11： | 0 |
| 2 | Deep Learning Approach for Automatic Cardiovascular Disease Prediction Employing ECG Signals显示文摘Cardiovascular problems have become the predominant cause of death worldwide and a rise in the number of patients has been observed lately.Currently,electrocardiogram(ECG)data is analyzed by medical experts to determine the cardiac abnormality,which is time-consuming.In addition,the diagnosis requires experienced medical experts and is error-prone.However,automated identification of cardiovascular disease using ECGs is a challenging problem and state-of-the-art performance has been attained by complex deep learning architectures.This study proposes a simple multilayer perceptron(MLP)model for heart disease prediction to reduce computational complexity.ECG dataset containing averaged signals with window size 10 is used as an input.Several competing deep learning and machine learning models are used for comparison.K-fold cross-validation is used to validate the results.Experimental outcomes reveal that the MLP-based architecture can produce better outcomes than existing approaches with a 94.40%accuracy score.The findings of this study show that the proposed system achieves high performance indicating that it has the potential for deployment in a real-world,practical medical environment. | Muhammad Tayyeb Muhammad Umer Khaled Alnowaiser Saima Sadiq Ala’Abdulmajid Eshmawi Rizwan Majeed Abdullah Mohamed Houbing Song Imran Ashraf | 2023 | Computer Modeling in Engineering & Sciences2023，，11： | 0 |
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