A5020962218- Diverticular Disease and Complications
- Organ Donation and Transplantation
- Artificial Intelligence in Healthcare and Education
- Renal Transplantation Outcomes and Treatments
- Insurance, Mortality, Demography, Risk Management
- Assisted Reproductive Technology and Twin Pregnancy
- Cystic Fibrosis Research Advances
- Hepatitis B Virus Studies
- Polyomavirus and related diseases
- Chronic Kidney Disease and Diabetes
- Respiratory Support and Mechanisms
- Traumatic Brain Injury and Neurovascular Disturbances
- Breast Cancer Treatment Studies
- Respiratory viral infections research
- Ovarian function and disorders
- Cardiac, Anesthesia and Surgical Outcomes
- Diagnosis and treatment of tuberculosis
- Liver Disease Diagnosis and Treatment
- Hepatitis C virus research
- Spinal Hematomas and Complications
- Genetic Syndromes and Imprinting
- Spine and Intervertebral Disc Pathology
- Cytomegalovirus and herpesvirus research
- Renal and Vascular Pathologies
- demographic modeling and climate adaptation
Institut de Cancérologie de Lorraine
2018
Institut Bergonié
2018
Centre Léon Bérard
2018
Centre Oscar Lambret
2018
Institut Curie
2018
Institut Jean Godinot
2018
Institut de Cancérologie de l'Ouest
2018
Hôpital Cochin
2014
Physiopathologie et Epidémiologie des Maladies Respiratoires
2014
Centre Hospitalier Ibn Sina
2005-2008
Artificial intelligence (AI) models analyzing embryo time-lapse images have been developed to predict the likelihood of pregnancy following in vitro fertilization (IVF). However, limited research exists on methods ensuring AI consistency and reliability clinical settings during its development validation process. We present a methodology for developing validating an model across multiple datasets demonstrate reliable performance evaluating blastocyst-stage embryos. This multicenter analysis...
Abstract Study question What is the impact of AI-based embryo triage on number IVF cycles needed to reach fetal heartbeat (FH)? Summary answer Simulated cohort ranking via AIVF Day-5 AI model demonstrates a 27.5% reduction in achieve FH. known already Published reports show FH rates per first-time IVF/single euploid transfer ranging from 26-43% (age <38 yrs). Likewise, average autologous retrieval required for 2.25±0.8, depending oocyte age and demographic. While conventional...
<title>Abstract</title> Background Artificial intelligence (AI) models analyzing embryo time-lapse images have been developed to predict the likelihood of pregnancy following in vitro fertilization (IVF). However, limited research exists on methods ensuring AI consistency and reliability clinical settings during its development validation process. We present a methodology for developing validating an model across multiple datasets demonstrate reliable performance evaluating blastocyst-stage...
Abstract Study question Can EMATM (AIVF, Israel) artificial intelligence (AI) platform provide personalized success estimates based on the patient’s metadata and embryonic development? Summary answer Individual patients can be given an accurate estimation of their chances for a clinical pregnancy using AI-based embryo evaluation patient metadata. What is known already: AI models are trained diverse datasets data from multiple clinics with varying ages history. Precision medicine attained by...
Abstract Background There is no large prospective trial assessing mid-term adverse effects of adjuvant chemotherapy. In order to address this question, we developed CANTO (CANcer TOxicities - NCT01993498 http://etudecanto.org/), a dedicated the quantification side after treatment for patients with early breast cancer and develop predictors such toxicities. The aim presentation assess chemotherapy (CT) practice report toxicities that persist 3-6 months CT. Methods study enrolling newly...