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| 1 | Beta cell function declines with age in glucose tolerant Caucasians显示文摘 | Chiu KC Lee NP Chohan P | 2000 | Clin Endocr2000，53，： | 1 |
| 2 | Parthenogenesis and somatic cell nuclear transfer in sheep oocytes using polscope显示文摘 | Nandedkar P Chohan P Patwardhan A | 2009 | Indian J Exp Biol2009，47，7： | 1 |
| 3 | L-arginine administration recovers sarcoplasmic reticulum function in ischemic reperfused hearts by preventing calpain activation 显示文摘 | CHOHAN P K SINGH R B DHALLA N S | 2006 | Cardiovasc Res2006，69，1： | 1 |
| 4 | The sarcoplasmic reticulum proteins are targets for calpain action in the ischemic-reperfused heart 显示文摘 | SINGH R B CHOHAN P K DHALLA N S | 2004 | J Mol Cell Cardiol2004，37，1： | 1 |
| 5 | Follow-up computed tomography scan in post-COVID-19 pneumonia显示文摘The coronavirus disease 2019(COVID-19)global pandemic can be a severe illness that leads to morbidity and mortality.With the increasing number of COVID-19 pneumonia survivors,several long-term changes may persist,including abnormal imaging of lung parenchyma.In addition to the clinical course,it is vital to follow up on pulmonary imaging during the post-infectious period,which is not routinely required in other common pulmonary diagnoses.Computed tomography(CT)scan of the chest is an effective and diagnostic tool for pneumonia which gives an insight into structural abnormalities within the lungs,complications,and possible progression of the disease.Several studies have monitored COVID-19 pneumonia and its complications using serial CT chest imaging from the initial phase of infection,hospitalization,and post-discharge.Nonetheless,long-term follow-up imaging data in post-COVID-19 is still limited.We have summarized the findings utilizing a systematic review of the literature regarding COVID-19 pneumonia imaging,including long-term follow-up. | Asad Chohan Saiara Choudhury Rahul Dadhwal Abhay P Vakil Rene Franco Pahnwat Tonya Taweesedt | 2022 | World Journal of Radiology2022，14，4： | 0 |
| 6 | Applications of artificial intelligence in common pulmonary diseases显示文摘Artificial intelligence(AI)is a branch of computer science where machines are trained to imitate human-level intelligence and perform well-defined tasks.AI can provide accurate results as well as analyze vast amounts of data that cannot be analyzed via conventional statistical methods.AI has been utilized in pulmonary medicine for almost two decades and its utilization continues to expand.AI can help in making diagnoses and predicting outcomes in pulmonary diseases based on clinical data,chest imaging,lung pathology,and pulmonary function testing.AI-based applications enable physicians to use enormous amounts of data and improve their precision in the treatment of pulmonary diseases.Given the growing role of AI in pulmonary medicine,it is important for practitioners caring for patients with pulmonary diseases to understand how AI can work in order to implement it into clinical practices and improve patient care.The goal of this mini-review is to discuss the use of AI in pulmonary medicine and imaging in cases of obstructive lung disease,interstitial lung disease,infections,nodules,and lung cancer. | Saiara Choudhury Asad Chohan Rahul Dadhwal Abhay P Vakil Rene Franco Pahnwat Tonya Taweesedt | 2022 | Artificial Intelligence in Medical Imaging2022，3，1： | 0 |
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