Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria.

Background: In malignant pleural mesothelioma (MPM), complex tumour morphology results in inconsistent radiological response assessment. Promising volumetric methods require automation to be practical. We developed a fully automated Convolutional Neural Network (CNN) for this purpose, performed blinded validation and compared CNN and human response classification and survival prediction in patients treated with chemotherapy.

Comparing performance on the Months of the Year Backwards test in hospitalised patients with delirium, dementia, and no cognitive impairment: an exploratory study.

Purpose: To investigate performance of the Months of the Year Backwards (MOTYB) test in older hospitalised patients with delirium, dementia, and no cognitive impairment.

Methods: Secondary analysis of data from a case-control study of 149 hospitalised patients aged ≥ 65 years with delirium [with or without dementia (N = 50)], dementia [without delirium (N = 46)], and no cognitive impairment (N = 53). Verbatim transcripts of MOTYB audio recordings were analysed to determine group differences in response patterns.

A smartphone-based test for the assessment of attention deficits in delirium: A case-control diagnostic test accuracy study in older hospitalised patients.

Background: Delirium is a common and serious acute neuropsychiatric syndrome which is often missed in routine clinical care. Inattention is the core cognitive feature. Diagnostic test accuracy (including cut-points) of a smartphone Delirium App (DelApp) for assessing attention deficits was assessed in older hospital inpatients.

Diagnostic test accuracy of a novel smartphone application for the assessment of attention deficits in delirium in older hospitalised patients: a prospective cohort study protocol.

Background: Delirium is a common and serious clinical syndrome which is often missed in routine clinical care. The core cognitive feature is inattention. We developed a novel bedside neuropsychological test for assessing inattention in delirium implemented on a smartphone platform (DelApp).

A wall-less poly(vinyl alcohol) cryogel flow phantom with accurate scattering properties for transcranial Doppler ultrasound propagation channels analysis.

Medical phantoms are frequently required to verify image and signal processing systems, and are often used to support algorithm development for a wide range of imaging and blood flow assessments. A phantom with accurate scattering properties is a crucial requirement when assessing the effects of multi-path propagation channels during the development of complex signal processing techniques for Transcranial Doppler (TCD) ultrasound. The simulation of physiological blood flow in a phantom with tissue and blood equivalence can be achieved using a variety of techniques.

Development of Android apps for cognitive assessment of dementia and delirium.

The next generation of medical technology applications for hand-held portable platforms will provide a core change in performance and sophistication, transforming the way health care professionals interact with patients. This advance is particularly apparent in the delivery of cognitive patient assessments, where smartphones and tablet computers are being used to assess complex neurological conditions to provide objective, accurate and reproducible test results. This paper reports on two such applications (apps) that have been developed to assist healthcare professionals with the detection and diagnosis of dementia and delirium.