The role of noise in denoising models for anomaly detection in medical images.

Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are difficult to acquire. Therefore, unsupervised anomaly detection approaches have been proposed using only normal data for training, with the aim of detecting outlier anomalous voxels at test time.

Acute stroke CDS: automatic retrieval of thrombolysis contraindications from unstructured clinical letters.

Introduction: Thrombolysis treatment for acute ischaemic stroke can lead to better outcomes if administered early enough. However, contraindications exist which put the patient at greater risk of a bleed (e.g.

Survey: Leakage and Privacy at Inference Time.

Leakage of data from publicly available Machine Learning (ML) models is an area of growing significance since commercial and government applications of ML can draw on multiple sources of data, potentially including users' and clients' sensitive data. We provide a comprehensive survey of contemporary advances on several fronts, covering involuntary data leakage which is natural to ML models, potential malicious leakage which is caused by privacy attacks, and currently available defence mechanisms. We focus on inference-time leakage, as the most likely scenario for publicly available models.

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).

Development and feasibility of a smartphone-based test for the objective detection and monitoring of attention impairments in delirium in the ICU.

Purpose: Delirium in the ICU is under-diagnosed. We evaluated feasibility and performance of a novel smartphone-based test for objectively detecting inattention in delirium.

Material And Methods: DelApp-ICU combines a behavioural assessment and an attention task, whereby participants follow simple commands and count serially presented circles (score range 0-12, lower scores indicating worse performance).

Accuracy and Feasibility of an Android-Based Digital Assessment Tool for Post Stroke Visual Disorders-The StrokeVision App.

Background: Visual impairment affects up to 70% of stroke survivors. We designed an app (StrokeVision) to facilitate screening for common post stroke visual issues (acuity, visual fields, and visual inattention). We sought to describe the test time, feasibility, acceptability, and accuracy of our app-based digital visual assessments against (a) current methods used for bedside screening and (b) gold standard measures.

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 a smartphone application for the objective detection of attentional deficits in delirium.

Background: Delirium is an acute, severe deterioration in mental functioning. Inattention is the core feature, yet there are few objective methods for assessing attentional deficits in delirium. We previously developed a novel, graded test for objectively detecting inattention in delirium, implemented on a computerized device (Edinburgh Delirium Test Box (EDTB)).

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.

Waist belt and central obesity cause partial hiatus hernia and short-segment acid reflux in asymptomatic volunteers.

Objective: There is a high incidence of inflammation and metaplasia at the gastro-oesophageal junction (GOJ) in asymptomatic volunteers. Additionally, the majority of patients with GOJ adenocarcinomas have no history of reflux symptoms. We report the effects of waist belt and increased waist circumference (WC) on the physiology of the GOJ in asymptomatic volunteers.

On the evolutionary and ontogenetic origins of tool-oriented behaviour in New Caledonian crows ().

New Caledonian crows () are prolific tool users in captivity and in the wild, and have an inherited predisposition to express tool-oriented behaviours. To further understand the evolution and development of tool use, we compared the development of object manipulation in New Caledonian crows and common ravens (), which do not routinely use tools. We found striking qualitative similarities in the ontogeny of tool-oriented behaviour in New Caledonian crows and food-caching behaviour in ravens.

New Caledonian crows use tools for non-foraging activities.

Tool use is of great interest for cognitive research, largely because it can be particularly revealing about the underlying information processing mechanisms. Tool use that is inflexible or requires extensive experience to change, and that is only addressed towards specific targets such as food, is not likely to reflect unusual or particularly complex cognition. On the contrary, if tools are employed flexibly and for a variety of innovative purposes, then conventional combinations of inherited predispositions and associative learning are challenged and interesting questions emerge.

Infection of Harmonia axyridis (Coleoptera: Coccinellidae) by Hesperomyces virescens (Ascomycetes: Laboulbeniales): role of mating status and aggregation behavior.

The ectoparasitic fungus Hesperomyces virescens was studied on Harmonia axyridis in North Carolina, in the southeastern United States. A primary goal was to investigate transmission of the disease by examining the correlation between the pattern of fungal infection and seasonal change in host behavior. Beetles were collected as they arrived at their winter quarters at two sites; in one site they were also subsampled at mid- and late winter.