Publications by authors named "D Hartl"
Previous analyses provide an industry benchmark of ∼10% for the success rate in clinical development. However, prior analyses were limited by a narrow timeframe, a diverse research focus, biases in phase-to-phase transition methodology or a focus on specific use cases. We calculated unbiased input:output ratios (Phase I to FDA new drug approval) to analyze the likelihood of first approval using data from clinicaltrials.
View Article and Find Full Text PDFPathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent (IBD) is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, IBD can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for quantitative-trait-locus experiments.
View Article and Find Full Text PDFThe incidence of follicular-derived thyroid cancers has increased worldwide in recent decades, mainly papillary thyroid cancers at low recurrence risk. A process of de-escalation in the initial management and follow-up of these patients has therefore been implemented in parallel. This article provides the best practice recommendations made by the French learned societies (Société française d'endocrinologie, Société française de médecine nucléaire, Association française de chirurgie endocrine, Société française d'oto-rhino-laryngologie et de chirurgie de la face et du cou), european and international learned societies (European Society for Medical Oncology and the American Thyroid Association), in the management of follicular-derived thyroid cancer without distant metastases.
View Article and Find Full Text PDFArticle Synopsis
- * NIFTP is diagnosed through histological examination, avoiding high-risk mutations, and has a low chance of recurrence, leading to less aggressive surgical treatment strategies compared to traditional thyroid cancers.
- * The review aims to provide a detailed overview of NIFTP, covering its characteristics, diagnosis, management, and future research possibilities while highlighting challenges in improving preoperative diagnostics and follow-up care.
Article Synopsis
- * This paper aims to create a machine learning algorithm using MRI characteristics to classify parotid gland tumors and compares its effectiveness against diagnoses made by junior and senior radiologists, incorporating data from 134 patients.
- * The study's random forest model achieved notable accuracy (0.720) and improved diagnostic abilities for junior radiologists by 6%, suggesting the algorithm could enhance the identification of tumor types and reduce the need for invasive procedures, though further research is needed for routine implementation.