ODD-Net: a hybrid deep learning architecture for image dehazing.

Haze can significantly reduce visibility and contrast of images captured outdoors, necessitating the enhancement of images. This degradation in image quality can adversely affect various applications, including autonomous driving, object detection, and surveillance, where poor visibility may lead to navigation errors and obscure crucial details. Existing dehazing techniques face several challenges: spatial methods tend to be computationally heavy, transform methods often fall short in quality, hybrid methods can be intricate and demanding, and deep learning methods require extensive datasets and computational power.

Customised 96-ocular TaqMan (iCAM) microarray PCR card for rapid diagnosis of microbial keratitis.

Aim: To validate the diagnostic performance of a custom 96-micro-organism TaqMan PCR card (iCAM) for microbial keratitis (MK) from a single corneal epithelial sample.

Methods: Patients over the age of 18 referred to Cambridge University Hospital with MK were recruited in this single-site prospective cohort study between September 2021 and January 2023. An ocular-specific, customised microarray card (iCAM) was constructed according to primer and probe nucleotide sequences developed in our department to detect bacteria, viruses, and fungi commonly implicated in MK using a single corneal epithelial sample.

Barriers to Total Joint Arthroplasty: A Comparison of High-Poverty and Low-Poverty Communities.

Objective: Our aim was to determine the most significant barriers to total joint arthroplasty (TJA) for people living in high-poverty communities relative to low-poverty communities.

Methods: We created a 21-question survey based on interviews with underrepresented minority patients with osteoarthritis targeting five barriers to TJA: trust in surgeon, recovery concerns, cost and/or insurance issues, fear of poor surgical outcomes, and timing considerations. Participants rated the importance of each barrier on a 5-point Likert scale, dichotomized into "very or extremely important" and "not as important.

Serum proteomics for the identification of biomarkers to flag predilection of COVID19 patients to various organ morbidities.

Background: COVID19 is a pandemic that has affected millions around the world since March 2020. While many patients recovered completely with mild illness, many patients succumbed to various organ morbidities. This heterogeneity in the clinical presentation of COVID19 infection has posed a challenge to clinicians around the world.