Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the progress of the discipline. In this paper we describe and critically assess the different ways AI systems are evaluated, and the role of components and techniques in these systems. We first focus on the traditional task-oriented evaluation approach. We identify three kinds of evaluation: human discrimination, problem benchmarks and peer confrontation. We describe some of the limitations of the many evaluation schemes and competitions in these three categories, and follow the progression of some of these tests. We then focus on a less customary (and challenging) ability-oriented evaluation approach, where a system is characterised by its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several possibilities: the adaptation of cognitive tests used for humans and animals, the development of tests derived from algorithmic information theory or more integrated approaches under the perspective of universal psychometrics. We analyse some evaluation tests from AI that are better positioned for an ability-oriented evaluation and discuss how their problems and limitations can possibly be addressed with some of the tools and ideas that appear within the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. 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Characteristics of Adults in the Hepatitis B Research Network in North America Reflect Their Country of Origin and Hepatitis B Virus Genotype

Chronic hepatitis B virus (HBV) infection is an important cause of cirrhosis and hepatocellular carcinoma worldwide; populations that migrate to the US and Canada might be disproportionately affected. The Hepatitis B Research Network (HBRN) is a cooperative network of investigators from the United States and Canada, created to facilitate clinical, therapeutic, and translational research in adults and children with hepatitis B. We describe the structure of the network and baseline characteristics of adults with hepatitis B enrolled in the network

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Presymptomatic Lesion in Childhood Cerebral Adrenoleukodystrophy: Timing and Treatment

Background and ObjectivesWe sought to characterize the natural history and standard-of-care practices between the radiologic appearance of brain lesions, the appearance of lesional enhancement, and treatment with hematopoietic stem-cell transplant or gene therapy among boys diagnosed with presymptomatic childhood-onset cerebral adrenoleukodystrophy (CCALD).MethodsWe analyzed a multicenter, mixed retrospective/prospective cohort of patients diagnosed with presymptomatic CCALD (Neurologic Function Score = 0, Loes Score [LS] = 0.5-9.0, and age <13 years). Two time-to-event survival analyses were conducted: (1) time from CCALD lesion onset-to-lesional enhancement and (2) time from enhancement-to-treatment. The analysis was repeated in the subset of patients with (1) the earliest evidence of CCALD, defined as an MRI LS ≤ 1, and (2) patients diagnosed between 2016 and 2021.ResultsSeventy-one boys were diagnosed with presymptomatic cerebral lesions at a median age of 6.4 years [2.4-12.1] with a LS of 1.5 [0.5-9.0]. Fifty percent of patients had lesional enhancement at diagnosis. In the remaining 50%, the median Kaplan-Meier (KM)-estimate of time from diagnosis-to-lesional enhancement was 6.0 months (95% CI 3.6-17.8). The median KM-estimate of time from enhancement-to-treatment is 3.8 months (95% CI 2.8-5.9); 2 patients (4.2%) developed symptoms before treatment. Patients with a diagnostic LS ≤ 1 were younger (5.8 years [2.4-11.5]), had a time-to-enhancement of 4.7 months (95% CI 2.7-9.30), and were treated in 3.8 months (95% CI 3.1-7.1); no patients developed symptoms before treatment. Time from CCALD diagnosis-to-treatment decreased over the course of the study (ρ =-0.401, p = 0.003).DiscussionOur findings offer a more refined understanding of the timing of lesion formation, enhancement, and treatment among boys with presymptomatic CCALD. These data offer benchmarks for standardizing clinical care and designing future clinical trials