XAI approach for addressing the dataset shift problem: BCI as a case study

In the Machine Learning (ML) literature, a well-known problem is the Dataset Shift problem where, differently from the ML standard hypothesis, the data in the training and test sets can follow different probability distributions leading ML systems toward poor generalisation performances. Therefore, such systems can be unreliable and risky, particularly when used in safety-critical domains. This problem is intensely felt in the Brain-Computer Interface (BCI) context, where bio-signals as Electroencephalographic (EEG) are used. In fact, EEG signals are highly non-stationary signals both over time and between different subjects. Despite several efforts in developing BCI systems to deal with different acquisition times or subjects, performance in many BCI applications remains low. Exploiting the knowledge from eXplainable Artificial Intelligence (XAI) methods can help develop EEG-based AI approaches, overcoming the performance returned by the current ones. The proposed framework will give greater robustness and reliability to BCI systems with respect to the current state of the art, alleviating the dataset shift problem and allowing a BCI system to be used by different subjects at different times without the need for further calibration/training stages

Toward the application of XAI methods in EEG-based systems

An interesting case of the well-known Dataset Shift Problem is the classification of Electroencephalogram (EEG) signals in the context of Brain-Computer Interface (BCI). The non-stationarity of EEG signals can lead to poor generalisation performance in BCI classification systems used in different sessions, also from the same subject. In this paper, we start from the hypothesis that the Dataset Shift problem can be alleviated by exploiting suitable eXplainable Artificial Intelligence (XAI) methods to locate and transform the relevant characteristics of the input for the goal of classification. In particular, we focus on an experimental analysis of explanations produced by several XAI methods on an ML system trained on a typical EEG dataset for emotion recognition. Results show that many relevant components found by XAI methods are shared across the sessions and can be used to build a system able to generalise better. However, relevant components of the input signal also appear to be highly dependent on the input itself

Digital image analysis of collagen assessment of progression of fibrosis in recurrent HCV after liver transplantation

Background & Aims: Histological assessment of fibrosis progression is currently performed by staging systems which are not continuous quantitative measurements. We aimed at assessing a quantitative measurement of fibrosis collagen proportionate area (CPA), to evaluate fibrosis progression and compare it to Ishak stage progression. Methods: We studied a consecutive cohort of 155 patients with recurrent HCV hepatitis after liver transplantation (LT), who had liver biopsies at one year and were subsequently evaluated for progression of fibrosis using CPA and Ishak staging, and correlated with clinical decompensation. The upper quartile of distribution of fibrosis rates (difference in CPA or Ishak stage between paired biopsies) defined fast fibrosers. Results: Patients had 610 biopsies and a median follow-up of 116 (18-252) months. Decompensation occurred in 29 (18%) patients. Median Ishak stage progression rate was 0.42 units/year: (24 (15%) fast fibrosers). Median CPA fibrosis progression rate was 0.71%/year (36 (23%) fast fibrosers). Clinical decompensation was independently associated by Cox regression only with CPA (p = 0.007), with AUROCs of 0.81 (95% CI 0.71-0.91) compared to 0.68 (95% CI 0.56-0.81) for Ishak stage. Fast fibrosis defined by CPA progression was independently associated with histological de novo hepatitis (OR: 3.77), older donor age (OR: 1.03) and non-use/discontinuation of azathioprine before 1 year post-LT (OR: 3.85), whereas when defined by Ishak progression, fast fibrosers was only associated with histological de novo hepatitis. Conclusions: CPA fibrosis progression rate is a better predictor of clinical outcome than progression by Ishak stage. Histological de novo hepatitis, older donor age and non-use/discontinuation of azathioprine are associated with rapid fibrosis progression in recurrent HCV chronic hepatitis after liver transplantation. © 2012 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved

Thrombosis, major bleeding, and survival in COVID-19 supported by VV- ECMO in the first vs second wave- multicentre observational study in the UK

BACKGROUND: Bleeding and thrombosis are major complications of veno-venous extracorporeal membrane (VV-ECMO). OBJECTIVES: To assess thrombosis, major bleeding (MB) and 180-day in patients supported by VV-ECMO between first (1st March-31st May 2020) and second (1st June 2020-30th June 2021) waves of the COVID-19 pandemic. PATIENTS/METHODS: Observational study of 309 consecutive patients (≥18years) with severe COVID-19 supported by VV-ECMO in four nationally commissioned ECMO centres, UK. RESULTS: Median age was 48 (19-75)years and 70.6% were male. Probabilities of survival, thrombosis, and MB at 180 days in the overall cohort were 62.5% (193/309), 39.8%(123/309) and 30%(93/309). In multivariate analysis, age >55 years (HR 2.29 [1.33-3.93],p=0.003) and elevated creatinine (HR 1.91 [1.19-3.08],p=0.008) were associated with increased mortality. Corrected for duration of VV-ECMO support, arterial thrombosis alone (HR 3.0 [95% CI1.5-5.9], P= 0.002) or circuit thrombosis alone (HR 3.9 [95% 2.4-6.3], P<0.001), but not venous thrombosis, increased mortality. MB during ECMO had 3-fold risk (95% CI 2.6-5.8, P<0.001) of mortality. The first wave cohort had more males (76.7% vs 64%, p=0.014), higher 180-day survival (71.1% vs 53.3% p=0.003), more venous thrombosis alone (46.4% vs 29.2%, p=0.02) and lower circuit thrombosis (9.2% vs 28.1%, p<0.001). The second wave cohort received more steroids (121/150 [80.6%] vs 86/159 [54.1%], p<0.0001) and Tocilizumab (20/150 [13.3%] vs 4/159 [2.5%] p=0.005). CONCLUSIONS: MB and thrombosis are frequent complications in patients on VV-ECMO and significantly increase mortality. Arterial thrombosis alone or circuit thrombosis alone increased mortality whilst venous thrombosis alone had no effect. MB during ECMO support increased mortality 3.9-fold

Role of Renal Biopsy in the Management of Renal Cancer: Concordance between Ultrasound/CT-Guided Biopsy Results and Definitive Pathology, Adverse Events, and Complication Rate

\ua9 2023 by the authors.(1) Background: In the last decade, the number of detected renal cancer cases has increased, with the highest incidence in Western countries. Although renal biopsy is reported as a safe procedure, it is not adopted in all centres. As it is not possible to accurately distinguish benign tumours using imaging, this may lead to overtreatment. Most of the cancer detected on imaging is treated by surgery, radiofrequency ablation (RFA), or cryotherapy. (2) Methods: This was a single-centre retrospective study of 225 patients studied preoperatively with ultrasound (US)/CT-guided renal biopsy, with the aim of supporting clinical management. Decisions regarding the biopsy were based on either MDT indication or physician preference. US-guided renal biopsy was the first option for all patients; CT-guided biopsy was used when US-guided biopsy was not feasible. The efficacy of renal biopsy in terms of diagnostic performance and the concordance between biopsy results and definitive pathology were investigated. Additionally, adverse events related to the biopsy were recorded and analysed. Data collected throughout the study were analysed using binary logistic regression, Fisher’s exact test, and Pearson’s chi-square test to investigate possible correlations between post-procedural complications and the size of the lesion. (3) Results: Renal biopsy was not diagnostic in 23/225 (10.2%) patients. A CT-guided approach was necessary in 20/225 patients after failure of US-guided biopsy. The complication rate of renal biopsy was 4.8% overall—all Clavien grade I and without any serious sequelae. Interestingly, complications occurred in patients with very different sizes of renal cell carcinoma. No correlation between complications and anticoagulant/antiplatelet drugs was found. No seeding was reported among the patients who underwent partial/radical nephrectomy. (4) Conclusions: Renal biopsy was shown to be safe and effective, with a high concordance between biopsy results and definitive pathology and a low rate of complications. The use of a CT-guided approach whenever the US-guided approach failed improved the diagnostic performance of renal biopsy