A pathologist-AI collaboration framework for enhancing diagnostic accuracies and efficiencies.

In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by limitations in data collection and in model transparency and interpretability. Here we describe a digital pathology framework, nuclei.io, that incorporates active learning and human-in-the-loop real-time feedback for the rapid creation of diverse datasets and models.

Uterine injury during diestrus leads to placental and embryonic defects in future pregnancies in mice†.

Uterine injury from procedures such as Cesarean sections (C-sections) often have severe consequences on subsequent pregnancy outcomes, leading to disorders such as placenta previa, placenta accreta, and infertility. With rates of C-section at ~30% of deliveries in the USA and projected to continue to climb, a deeper understanding of the mechanisms by which these pregnancy disorders arise and opportunities for intervention are needed. Here we describe a rodent model of uterine injury on subsequent in utero outcomes.

Clinical Features of SARS-CoV-2 Infection During Pregnancy and Associated Placental Pathologies.

We reviewed the clinicopathologic findings of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-exposed placentas at our institution. We identified patients diagnosed with SARS-CoV-2 during pregnancy (March-October 2020). Clinical data included gestational age at diagnosis and delivery and maternal symptoms.