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Huguette S Brink, Aart Jan van der Lely and Joke van der Linden

GD pathogenesis. Combining biomarkers and risk factors into a predictive model may add to early prediction of GD, evoke effective prevention strategies and may ultimately reduce complications associated with GD. The aim of this review is to ( 1

Open access

Hui Long, Yanhong Nie, Li Wang, Yong Lu, Yan Wang, Yijun Cai, Zhen Liu, Miaomiao Jia, Qifeng Lyu, Yanping Kuang and Qiang Sun

FSH level ( 10 ). To date, AMH is widely used in prediction of ovarian response and clinical outcomes in humans ( 19 ) and other species, such as cow ( 20 ), sheep ( 21 ) and goats ( 22 ). However, the role of AMH in prediction of ovarian response in

Open access

Ashley K Clift, Omar Faiz, Robert Goldin, John Martin, Harpreet Wasan, Marc-Olaf Liedke, Erik Schloericke, Anna Malczewska, Guido Rindi, Mark Kidd, Irvin M Modlin and Andrea Frilling

represent s.e.m. Data for all patients are included. The data marks in each plot from left to right represent high-, medium- and low-risk groups, respectively. Discussion NET patient prognosis prediction is limited by the paucity of

Open access

Marieke S Velema, Evie J M Linssen, Ad R M M Hermus, Hans J M M Groenewoud, Gert-Jan van der Wilt, Antonius E van Herwaarden, Jacques W M Lenders, Henri J L M Timmers and Jaap Deinum

development and validation of prediction models ( 5 ). Patients Our cohort consisted of adult patients who underwent an SLT for clinically suspected PA at the Radboud Adrenal Center, a tertiary center of expertise for patients with adrenal disorders in

Open access

Nidan Qiao

). Machine learning may help to build a more reliable aided diagnostic tool for neuroradiologists and neuropathologists. Better prediction of clinical outcomes in these patients may provide better clinical decision support for either neuroendocrinologists or

Open access

Yang Lv, Xu Han, Chunyan Zhang, Yuan Fang, Ning Pu, Yuan Ji, Dansong Wang, Xu Xuefeng and Wenhui Lou

surgical/needled specimen can give rise to the prognosis prediction and nonoperative management guidance to some extents, but this is usually based on a fixed small biopsy sample that may not reflect the heterogeneity present in advanced tumors ( 2

Open access

Urszula Smyczyńska, Joanna Smyczyńska, Maciej Hilczer, Renata Stawerska, Ryszard Tadeusiewicz and Andrzej Lewiński

, significant variability in its effectiveness in different patients is observed ( 1 , 2 ). Taking into account the inconsistent and sometimes disappointing effects of treatment, the need to create prediction models of growth response to GH therapy has been

Open access

Chao-bin He, Yu Zhang, Zhi-yuan Cai and Xiao-jun Lin

receiver operating characteristic (ROC) curve (AUC) were used to evaluate the 1-, 2- and 3-year survival predictions. Results Patient characteristics According to the whole criteria above, we identified 1966 eligible PNET patients diagnosed

Open access

Werner F Blum, Abdullah Alherbish, Afaf Alsagheir, Ahmed El Awwa, Walid Kaplan, Ekaterina Koledova and Martin O Savage

particularly in non-GH deficiency disorders such as Turner syndrome, short stature related to birth size small for gestational age (SGA) and idiopathic short stature ( 5 ), has led to development of prediction models of growth response ( 6 ) and a recognition

Open access

Yang Lv, Ning Pu, Wei-lin Mao, Wen-qi Chen, Huan-yu Wang, Xu Han, Yuan Ji, Lei Zhang, Da-yong Jin, Wen-Hui Lou and Xue-feng Xu

primary cohort to identify related prognostic factors affecting overall survival (OS) of rectal NEC patients and to construct nomogram for prognosis prediction for these patients. Besides, the internal and external validations were also performed to