Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.

Objective: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an AI algorithm that can effectively classify colonic biopsies into normal versus abnormal categories, designed to automatically report normal cases. We performed a retrospective pathological and clinical review of the errors made by IGUANA.

Large multimodal model-based standardisation of pathology reports with confidence and its prognostic significance.

Despite the existence of established standards and guidelines for pathology reporting, many pathology reports are still written in unstructured free text. Extracting information from these reports and formatting it according to a standard is crucial for consistent interpretation. Automated information extraction from unstructured pathology reports is a challenging task, as it requires accurately interpreting medical terminologies and context-dependent details.

Ultrastructural investigation of the posterior hyaloid membrane in posterior vitreous detachment.

Background: Separation of the posterior hyaloid membrane (PHM) from the retina in posterior vitreous detachment (PVD) is a fundamental, but poorly understood, process underlying vitreoretinal disorders including retinal detachment and macular hole. We performed electron microscopy studies of the PHM after PVD to investigate its ultrastructure, associated cellular structures and relationship to the internal limiting membrane (ILM).

Methods: Post-mortem human eyes were collected from recently deceased patients over 70 years of age.

What factors influence cellular pathologists' confidence in case reporting?

Histopathology is a challenging interpretive discipline, and the level of confidence a pathologist has in their diagnosis is known to vary, which is conveyed descriptively in pathology reports. There has been little study to accurately quantify pathologists' diagnostic confidence or the factors that influence it. In this study involving sixteen pathologists from six NHS trusts, we assessed diagnostic confidence across multiple variables and four specialties.