Artificial intelligence for automated detection of diabetic foot ulcers: A real-world proof-of-concept clinical evaluation.

Objective: Conduct a multicenter proof-of-concept clinical evaluation to assess the accuracy of an artificial intelligence system on a smartphone for automated detection of diabetic foot ulcers.

Methods: The evaluation was undertaken with patients with diabetes (n = 81) from September 2020 to January 2021. A total of 203 foot photographs were collected using a smartphone, analysed using the artificial intelligence system, and compared against expert clinician judgement, with 162 images showing at least one ulcer, and 41 showing no ulcer.

Fatal COVID-19 in a neonate after probable late intrauterine transmission.

We report the case of a 35-week gestation infant girl born by emergent cesarean section for fetal distress in a woman with recent coronavirus disease 2019 (COVID-19). Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polymerase chain reaction (PCR) on the infant at 24 and 48 hours of life were negative. However, at 72 hours of life, the infant's respiratory status worsened, and a repeat SARS-CoV-2 PCR was positive.