Publications by authors named "Francois Talbot"
Background: Pulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT), most of the time outside of lung cancer screening (LCS). We aimed to evaluate the number of incidental pulmonary nodules (IPN) found in 1 year in our hospital, as well as the follow-up (FUP) rate and the clinical and radiological features associated with FUP.
Methods: We trained a Natural Language Processing (NLP) tool to identify the transcripts mentioning the presence of a pulmonary nodule, among a large population of patients from a French hospital.
Background: Invasive candidiasis is still recognized as a major cause of morbidity and mortality. To support clinicians in the optimal use of antifungals for the treatment of invasive candidiasis, a computerized decision support system (CDSS) was developed based on institutional guidelines.
Objectives: To evaluate the correlation of this newly developed CDSS with clinical practices, we set-up a retrospective multicentre cohort study with the aim of providing the concordance rate between the CDSS recommendation and the medical prescription (NCT05656157).
Article Synopsis
- The study aimed to assess how lung lesion quantification from chest CT scans using AI impacts the prediction of death and ICU admission in COVID-19 patients.
- Data from 349 patients who tested positive for COVID-19 were analyzed, employing AI to measure lung lesion volume and determine the effectiveness of various models in predicting patient outcomes.
- Results showed that incorporating the lung lesion ratio significantly improved the accuracy of predictions for both death and ICU admission compared to models based only on clinical characteristics.
Rationale And Objectives: To develop a Natural Language Processing (NLP) method based on Bidirectional Encoder Representations from Transformers (BERT) adapted to French CT reports and to evaluate its performance to calculate the diagnostic yield of CT in patients with clinical suspicion of pulmonary embolism (PE).
Materials And Methods: All the CT reports performed in our institution in 2019 (99,510 reports, training and validation dataset) and 2018 (94,559 reports, testing dataset) were included after anonymization. Two BERT-based NLP sentence classifiers were trained on 27.
Objectives: To assess the diagnostic performances of chest CT for triage of patients in multiple emergency departments during COVID-19 epidemic, in comparison with reverse transcription polymerase chain reaction (RT-PCR) test.
Method: From March 3 to April 4, 2020, 694 consecutive patients from three emergency departments of a large university hospital, for which a hospitalization was planned whatever the reasons, i.e.