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This article reports the results of an experiment conducted with ChatGPT to see how its performance compares to human performance on tests that require specific knowledge and skills, such as university admission tests. We chose a general undergraduate admission test and two tests for admission to biomedical programs: the Scholastic Assessment Test (SAT), the Cambridge BioMedical Admission Test (BMAT), and the Italian Medical School Admission Test (IMSAT). In particular, we looked closely at the difference in performance between ChatGPT-4 and its predecessor, ChatGPT-3.5, to assess its evolution. The performance of ChatGPT-4 showed a significant improvement over ChatGPT-3.5 and, compared to real students, was on average within the top 10% in the SAT test, while the score in the IMSAT test granted admission to the two highest ranked Italian medical schools. In addition to the performance analysis, we provide a qualitative analysis of incorrect answers and a classification of three different types of logical and computational errors made by ChatGPT-4, which reveal important weaknesses of the model. This provides insight into the skills needed to use these models effectively despite their weaknesses, and also suggests possible applications of our analysis in the field of education., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Giunti et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Recent advances in Quantum Machine Learning (QML) have provided benefits to several computational processes, drastically reducing the time complexity. Another approach of combining quantum information theory with machine learning-without involving quantum computers-is known as Quantum-inspired Machine Learning (QiML), which exploits the expressive power of the quantum language to increase the accuracy of the process (rather than reducing the time complexity). In this work, we propose a large-scale experiment based on the application of a binary classifier inspired by quantum information theory to the biomedical imaging context in clonogenic assay evaluation to identify the most discriminative feature, allowing us to enhance cell colony segmentation. This innovative approach offers a two-fold result: (1) among the extracted and analyzed image features, homogeneity is shown to be a relevant feature in detecting challenging cell colonies; and (2) the proposed quantum-inspired classifier is a novel and outstanding methodology, compared to conventional machine learning classifiers, for the evaluation of clonogenic assays.

A holistic extension of classical propositional logic is introduced via Toffoli quantum gate. This extension is based on the framework of the so-called "quantum computation with mixed states", where also irreversible transformations are taken into account. Formal aspects of this new logical system are detailed: in particular, the concepts of tautology and contradiction are investigated in this extension. These concepts turn out to receive substantial changes due to the non-separability of some quantum states; as an example, Werner states emerge as particular cases of "holistic" contradiction.

This paper proposes a new quantum-like method for the binary classification applied to classical datasets. Inspired by the quantum Helstrom measurement, this innovative approach has enabled us to define a new classifier, called Helstrom Quantum Centroid (HQC). This binary classifier (inspired by the concept of distinguishability between quantum states) acts on density matrices-called density patterns-that are the quantum encoding of classical patterns of a dataset. In this paper we compare the performance of HQC with respect to twelve standard (linear and non-linear) classifiers over fourteen different datasets. The experimental results show that HQC outperforms the other classifiers when compared to the Balanced Accuracy and other statistical measures. Finally, we show that the performance of our classifier is positively correlated to the increase in the number of "quantum copies" of a pattern and the resulting tensor product thereof., Competing Interests: The authors have declared that no competing interests exist.

Quantum computation theory has inspired new forms of quantum logic, called quantum computational logics , where formulas are supposed to denote pieces of quantum information, while logical connectives are interpreted as special examples of quantum logical gates. The most natural semantics for these logics is a form of holistic semantics , where meanings behave in a contextual way. In this framework, the concept of quantum probability can assume different forms. We distinguish an absolute concept of probability, based on the idea of quantum truth , from a relative concept of probability (a form of transition-probability , connected with the notion of fidelity between quantum states). Quantum information has brought about some intriguing epistemic situations. A typical example is represented by teleportation-experiments. In some previous works we have studied a quantum version of the epistemic operations "to know", "to believe", "to understand". In this article, we investigate another epistemic operation (which is informally used in a number of interesting quantum situations): the operation "being probabilistically informed".

Parallelism represents an essential aspect of human mind/brain activities. One can recognize some common features between psychological parallelism and the characteristic parallel structures that arise in quantum theory and in quantum computation. The article is devoted to a discussion of the following questions: a comparison between classical probabilistic Turing machines and quantum Turing machines.possible applications of the quantum computational semantics to cognitive problems.parallelism in music.

Background: The use of antiretroviral drug abacavir (ABC) has been often associated with cutaneous hypersensitivity reactions, the majority being severe., Objective: The present study discusses the issues of patch testing associated with pharmacogenetic screening in light of the development of abacavir hypersensitivity reactions (HSRs)., Methods: The present authors classified 100 patients into three groups: 20 patients (group A) had experienced a hypersensitivity reaction when treated with highly active antiretroviral therapy (HAART) including ABC; 60 HIV-positive patients (group B) were receiving HAART scheme including ABC; 20 HIV-negative patients acted as control group (group C). Patients of group A and B were patch tested with ABC as such, then with an ABC extract diluted to 1 and 10% in petrolatum. Group C patients underwent patches with petrolatum only. A biopsy of the lesion was performed in those patients who showed a positive skin reaction. All patients had been tested for HLA-B5701., Results: A correlation between positive ABC-patch testing and HLA-B5701 was found in 50% of patients enrolled in group A, while in group B and C, all patients tested negative for both genetic marker and ABC-patch testing. Histopathology findings confirmed a vigorous CD4+ and CD8+ cellular response that is compatible with HSR., Conclusions: Patch testing is a safe and sensitive method that can be used for to confirm or exclude any correlation between abacavir and hypersensitivity skin reactions in patients who have been previously treated with abacavir during HAART. Correlation between patch test, immunohistochimical, and genetic tests results shows that genetic testing increases the possibility to identify patients with a true reaction., (© 2012 Wiley Periodicals, Inc.)

Background: Atazanavir (ATV) has demonstrated high efficacy and safety in both treatment-naïve and treatment-experienced patients. Some comparative data are available on the durability of ritonavir-boosted (ATV/r) and unboosted formulations, but there are no data on clinicians' motivations for choosing one or another in everyday practice. The aim of this study was to evaluate the long-term efficacy of boosted and unboosted ATV in a cohort of treatment-experienced patients., Methods: All patients included in the study were enrolled in an observational cohort within the Surveillance Cohort Long-Term Toxicity Antiretrovirals (SCOLTA) Project. Data on CD4 cell count, HIV viral load, metabolic parameters and adverse events of grade 3-4 are collected through an on-line system every six months. The duration of treatment with ATV was evaluated using the Kaplan-Meier curve and boosted and unboosted regimens were compared using the log-rank test., Results: A total of 509 patients starting ATV as a component of their antiretroviral therapy were enrolled in the SCOLTA Project at the time of the study. Boosted ATV was received by 379 patients (74.5%) while 130 (25.5%) were treated with the unboosted formulation. The last therapeutic regimen did not influence the choice of ATV formulation. The mean observational time was 23.9 months. At the end of follow-up, 58.5% of patients on unboosted ATV and 58.1% of patients on ATV/r continued the treatment and no statistically significant differences were observed for ATV durability between the formulations or among the single causes of therapy interruption., Conclusions: Our results suggest that, in unselected clinical settings, ATV-containing antiretroviral therapy is durable and safe in both its formulations.

The introduction of highly active antiretroviral therapy in 1995 dramatically decreased AIDS-related events and deaths rates; however, the enthusiasm among the medical and social community was soon limited by the growing incidence of various side-effects that often greatly limited patients' quality of life. The second problem caused by such a complex treatment consisted of sub-optimal adherence, with a consequent higher risk of the development of drug resistance.