Updating probabilistic epistemic states in persuasion dialogues

In persuasion dialogues, the ability of the persuader to model the persuadee allows the persuader to make better choices of move. The epistemic approach to probabilistic argumentation is a promising way of modelling the persuadee’s belief in arguments, and proposals have been made for update methods that specify how these beliefs can be updated at each step of the dialogue. However, there is a need to better understand these proposals, and moreover, to gain insights into the space of possible update functions. So in this paper, we present a general framework for update functions in which we consider existing and novel update functions

On the tradeoff between correctness and completeness in argumentative explainable AI

Explainable AI aims at making the decisions of autonomous systems human-understandable. Argumentation frameworks are a natural tool for this purpose. Among them, bipolar abstract argumentation frameworks seem well suited to explain the effect of features on a classification decision and their formal properties can potentially be used to derive formal guarantees for explanations. Two particular interesting properties are correctness (if the explanation says that X affects Y, then X affects Y ) and completeness (if X affects Y, then the explanation says that X affects Y ). The reinforcement property of bipolar argumentation frameworks has been used as a natural correctness counterpart in previous work. Applied to the classification context, it basically states that attacking features should decrease and supporting features should increase the confidence of a classifier. In this short discussion paper, we revisit this idea, discuss potential limitations when considering reinforcement without a corresponding completeness property and how these limitations can potentially be overcome

Prostate Radiofrequency Focal Ablation (ProRAFT) Trial: A Prospective Development Study Evaluating a Bipolar Radiofrequency Device to Treat Prostate Cancer

PURPOSE: To determine early efficacy of bipolar radiofrequency ablation with a coil design (bRFA) for focal ablation of clinically significant localised prostate cancer (sPCa)visible at mpMRI. MATERIAL AND METHODS: A prospective IDEAL phase 2 development study (NCT02294903) recruited treatment naive patients with a single focus of localised sPCa (Gleason 7 or 4 mm or more of Gleason 6) concordant with a lesion visible on multi-parametric MRI. Intervention was a focal ablation with a bRFA system (Encage®, Trod Medical) encompassing the lesion and a predefined margin using nonrigid MRI-ultrasound fusion. Primary outcome was the proportion of men with absence of sPCa on biopsy at 6 months. Trial follow up comprised serum PSA, mpMRI at 1 week, 6 and 12 months post ablation. Validated patient reported outcome measures (PROMs) for urinary, erectile and bowel functions and adverse events monitoring system were used. Analyses were done on a per-protocol basis. RESULTS: 20 of 21 patients recruited received the intervention. Baseline characteristics were a median age of 66 years (IQR 63-69), pre-operative median PSA of 7.9 ng/ml (5.3-9.6), 18 (90%) had Gleason 7 with median maximum cancer of 7 mm (IQR 5-10) for a median 2.8 cc mpMRI lesions (IQR 1.4-4.8). Targeted biopsy of the treated area (median number of cores=6, IQR 5-8) showed absence of sPCa in 16/20 men (80%), concordant with mpMRI. There was a low profile of side effects at PROMs analysis and no serious adverse events. CONCLUSIONS: Focal therapy of sPCa associated with an MRI lesion using bRFA showed early efficacy to ablate cancer with low rates of genitourinary and rectal side-effects

Protocol for a feasibility randomised controlled trial of targeted oxygen therapy in mechanically ventilated critically ill patients

IntroductionOxygen is the most commonly administered drug to mechanically ventilated critically ill adults, yet little is known about the optimum oxygen saturation (SpO2) target for these patients; the current standard of care is an SpO2of 96% or above. Small pilot studies have demonstrated that permissive hypoxaemia (aiming for a lower SpO2than normal by using a lower fractional inspired oxygen concentration (FIO2)) can be achieved in the critically ill and appears to be safe. This approach has not been evaluated in a National Health Service setting. It is possible that permissive hypoxaemia may be beneficial to critically ill patients thus it requires robust evaluation.Methods and analysisTargeted OXygen therapY in Critical illness (TOXYC) is a feasibility randomised controlled trial (RCT) to evaluate whether recruiting patients to a study of permissive hypoxaemia is possible in the UK. It will also investigate biological mechanisms that may underlie the links between oxygenation and patient outcomes. Mechanically ventilated patients with respiratory failure will be recruited from critical care units at two sites and randomised (1:1 ratio) to an SpO2target of either 88%–92% or ≥96% while intubated with an endotracheal tube. Clinical teams can adjust FIO2and ventilator settings as they wish to achieve these targets. Clinical information will be collected before, during and after the intervention and blood samples taken to measure markers of systemic oxidative stress. The primary outcome of this study is feasibility, which will be assessed by recruitment rate, protocol adherence and withdrawal rates. Secondary outcomes will include a comparison of standard critical care outcome measures between the two intervention groups, and the measurement of biomarkers of systemic oxidative stress. The results will be used to calculate a sample size, likely number of sites and overall length of time required for a subsequent large multicentre RCT.Ethics and disseminationThis study was approved by the London - Harrow Research Ethics Committee on 2 November 2017 (REC Reference 17/LO/1334) and received HRA approval on 13 November 2017. Results from this study will be disseminated in peer-reviewed journals, at medical and scientific meetings, in the NIHR Journals Library and patient information websites.Trial registration numberNCT03287466; Pre-results.</jats:sec

The SmartTarget BIOPSY trial: A prospective, within-person randomised, blinded trial comparing the accuracy of visual-registration and MRI/ultrasound image-fusion targeted biopsies for prostate cancer risk stratification

Background: Multiparametric magnetic resonance imaging (mpMRI)-targeted prostate biopsies can improve detection of clinically significant prostate cancer and decrease the overdetection of insignificant cancers. Whether visual-registration targeting is sufficient or if augmentation with image-fusion software is needed is unknown. Objective: To assess concordance between the two methods. Design, Setting, and Participants: We conducted a blinded, within-person randomised, paired validating clinical trial. From 2014 to 2016, 141 men who had undergone a prior (positive or negative) transrectal ultrasound biopsy and had a discrete lesion on mpMRI (score 3 to 5) requiring targeted transperineal biopsy were enrolled at a UK academic hospital; 129 underwent both biopsy strategies and completed the study. Intervention: The order of performing biopsies using visual-registration and a computer-assisted MRI/ultrasound image-fusion system (SmartTarget) on each patient was randomised. The equipment was reset between biopsy strategies to mitigate incorporation bias. Outcome Measurements and Statistical Analysis: The proportion of clinically significant prostate cancer (primary outcome: Gleason pattern ≥3+4=7, maximum cancer core length ≥4 mm; secondary outcome: Gleason pattern ≥4+3=7, maximum cancer core length ≥6 mm) detected by each method was compared using McNemar's test of paired proportions. Results and Limitations: The two strategies combined detected 93 clinically significant prostate cancers (72% of the cohort). Each strategy individually detected 80/93 (86%) of these cancers; each strategy detected 13 cases missed by the other. Three patients experienced adverse events related to biopsy (urinary retention, urinary tract infection, nausea and vomiting). No difference in urinary symptoms, erectile function, or quality of life between baseline and follow-up (median 10.5 weeks) was observed. The key limitation was lack of parallel-group randomisation and limit on number of targeted cores. Conclusions: Visual-registration and image-fusion targeting strategies combined had the highest detection rate for clinically significant cancers. Targeted prostate biopsy should be performed using both strategies together. Patient Summary: We compared two prostate cancer biopsy strategies: visual-registration and image-fusion. The combination of the two strategies found the most clinically important cancers and should be used together whenever targeted biopsy is being performed

The SmartTarget Biopsy Trial: A Prospective, Within-person Randomised, Blinded Trial Comparing the Accuracy of Visual-registration and Magnetic Resonance Imaging/Ultrasound Image-fusion Targeted Biopsies for Prostate Cancer Risk Stratification

Background: Multiparametric magnetic resonance imaging (mpMRI)-targeted prostate biopsies can improve detection of clinically significant prostate cancer and decrease the overdetection of insignificant cancers. It is unknown whether visual-registration targeting is sufficient or augmentation with image-fusion software is needed. Objective: To assess concordance between the two methods. Design, setting, and participants: We conducted a blinded, within-person randomised, paired validating clinical trial. From 2014 to 2016, 141 men who had undergone a prior (positive or negative) transrectal ultrasound biopsy and had a discrete lesion on mpMRI (score 3–5) requiring targeted transperineal biopsy were enrolled at a UK academic hospital; 129 underwent both biopsy strategies and completed the study. Intervention: The order of performing biopsies using visual registration and a computer-assisted MRI/ultrasound image-fusion system (SmartTarget) on each patient was randomised. The equipment was reset between biopsy strategies to mitigate incorporation bias. Outcome measurements and statistical analysis: The proportion of clinically significant prostate cancer (primary outcome: Gleason pattern ≥3 + 4 = 7, maximum cancer core length ≥4 mm; secondary outcome: Gleason pattern ≥4 + 3 = 7, maximum cancer core length ≥6 mm) detected by each method was compared using McNemar's test of paired proportions. Results and limitations: The two strategies combined detected 93 clinically significant prostate cancers (72% of the cohort). Each strategy detected 80/93 (86%) of these cancers; each strategy identified 13 cases missed by the other. Three patients experienced adverse events related to biopsy (urinary retention, urinary tract infection, nausea, and vomiting). No difference in urinary symptoms, erectile function, or quality of life between baseline and follow-up (median 10.5 wk) was observed. The key limitations were lack of parallel-group randomisation and a limit on the number of targeted cores. Conclusions: Visual-registration and image-fusion targeting strategies combined had the highest detection rate for clinically significant cancers. Targeted prostate biopsy should be performed using both strategies together. Patient summary: We compared two prostate cancer biopsy strategies: visual registration and image fusion. A combination of the two strategies found the most clinically important cancers and should be used together whenever targeted biopsy is being performed. Image-fusion results in a clinically significant prostate cancer detection rate were similar to those of visual registration performed by an experienced operator. Detection could be improved by 14% with no adverse effect on patient safety by adding image fusion to conventional visual-registration targeting

Explaining random forests using bipolar argumentation and Markov networks

Random forests are decision tree ensembles that can be used to solve a variety of machine learning problems. However, as the number of trees and their individual size can be large, their decision making process is often incomprehensible. We show that their decision process can be naturally represented as an argumentation problem, which allows creating global explanations via argumentative reasoning. We generalize sufficient and necessary argumentative explanations using a Markov network encoding, discuss the relevance of these explanations and establish relationships to families of abductive explanations from the literature. As the complexity of the explanation problems is high, we present an efficient approximation algorithm with probabilistic approximation guarantees

Understanding ProbLog as probabilistic argumentation

ProbLog is a popular probabilistic logic programming language and tool, widely used for applications requiring to deal with inherent uncertainties in structured domains. In this paper we study some connections between ProbLog and a variant of another well-known formalism combining symbolic reasoning and reasoning under uncertainty, namely probabilistic argumentation. Specifically, we show that ProbLog is an instance of a form of Probabilistic Abstract Argumentation (PAA) under the constellation approach, which builds upon Assumption-Based Argumentation (ABA). The connections pave the way towards equipping ProbLog with a variety of alternative semantics, inherited from PAA/PABA, as well as obtaining novel argumentation semantics for PAA/PABA, leveraging on existing connections between ProbLog and argumentation. Moreover, the connections pave the way towards novel forms of argumentative explanations for ProbLog’s outputs