AI and ML in accounting and finance: A bibliometric review

Artificial intelligence (AI) and machine learning (ML) are two related technologies in accounting and finance studies. This study maps the conceptual structure of AI and ML research with the aim of contributing to a better understanding of this research stream. A bibliometric analysis of 3,836 documents on ai and ML retrieved from the Web of Science database is conducted. The analysis of descriptive performance indicators identifies the main traits of the scientific debate about AI and ML in terms of publications, productive countries and sources. To map the conceptual structure of the dataset, the study performs a thematic evolution. The results highlight the growing academic interest in the research topic, especially in the past few years. The results of this study may provide scholars with a better understanding of AI and ML research in accounting and finance. This paper contributes to the field by providing an examination of the current state of the art of AI e ML research and identifying possible future research directions

AI and ML in accounting and finance: A bibliometric review

Artificial intelligence (AI) and machine learning (ML) are two related technologies in accounting and finance studies. This study maps the conceptual structure of AI and ML research with the aim of contributing to a better understanding of this research stream. A bibliometric analysis of 3,836 documents on ai and ML retrieved from the Web of Science database is conducted. The analysis of descriptive performance indicators identifies the main traits of the scientific debate about AI and ML in terms of publications, productive countries and sources. To map the conceptual structure of the dataset, the study performs a thematic evolution. The results highlight the growing academic interest in the research topic, especially in the past few years. The results of this study may provide scholars with a better understanding of AI and ML research in accounting and finance. This paper contributes to the field by providing an examination of the current state of the art of AI e ML research and identifying possible future research directions

Blockade of thrombopoietin reduces organ damage in experimental endotoxemia and polymicrobial sepsis

BACKGROUND AND PURPOSE:Thrombopoietin (TPO), a growth factor primarily involved in thrombopoiesis may also have a role in the pathophysiology of sepsis. In patients with sepsis, indeed, TPO levels are markedly increased, with disease severity being the major independent determinant of TPO concentrations. Moreover, TPO increases and correlates with ex vivo indices of platelet activation in patients with burn injury upon sepsis development, and may contribute to depress cardiac contractility in septic shock. Still, the role of TPO in sepsis pathophysiology remains controversial, given the protective role of TPO in other experimental disease models, for instance in doxorubicin-induced cardiotoxicity and myocardial ischemia/reperfusion injury. The aim of our study was to define the contribution of TPO in the development of organ damage induced by endotoxemia or sepsis, and to investigate the effects of inhibiting TPO in these conditions. METHODS:We synthesized a chimeric protein able to inhibit TPO, mTPOR-MBP, and studied its effect in two murine experimental models, acute endotoxemia and cecal ligation and puncture (CLP) model. RESULTS:In both models, TPO levels markedly increased, from 289.80±27.87 pg/mL to 465.60±45.92 pg/mL at 3 hours in the LPS model (P<0.01), and from 265.00±26.02 pg/mL to 373.70±26.20 pg/mL in the CLP model (P<0.05), respectively. Paralleling TPO levels, also platelet-monocyte aggregates increased, from 32.86±2.48% to 46.13±1.39% at 3 hours in the LPS model (P<0.01), and from 43.68±1.69% to 56.52±4.66% in the CLP model (P<0.05). Blockade of TPO by mTPOR-MBP administration reduced histological damage in target organs, namely lung, liver, and gut. In particular, neutrophil infiltration and lung septal thickening were reduced from a score of 1.86±0.34 to 0.60±0.27 (P<0.01) and from 1.43±0.37 to 0.40±0.16 (P<0.05), respectively, in the LPS model at 3 hours, and from a score of 1.75±0.37 to 0.38±0.18 (P<0.01) and from 1.25±0.31 to 0.13±0.13 (P<0.001), respectively, in the CLP model. Similarly, the number of hepatic microabscesses was decreased from 14.14±1.41 to 3.64±0.56 in the LPS model at 3 hours (P<0.001), and from 1.71±0.29 to 0.13±0.13 in the CLP model (P<0.001). Finally, the diameter of intestinal villi decreased from 90.69±3.95 μm to 70.74±3.60 μm in the LPS model at 3 hours (P<0.01), and from 74.29±4.29 μm to 57.50±1.89 μm in the CLP model (P<0.01). This protective effect was associated with the blunting of the increase in platelet-monocyte adhesion, and, on the contrary, with increased platelet-neutrophil aggregates in the circulation, which may be related to decreased neutrophil sequestration into the inflamed tissues. Conversely, circulating cytokine levels were not significantly changed, in both models, by mTPOR-MBP administration. CONCLUSION:Our results demonstrate that TPO participates in the development of organ damage induced by experimental endotoxemia or polymicrobial sepsis via a mechanism involving increased platelet-leukocyte adhesion, but not cytokine release, and suggest that blocking TPO may be useful in preventing organ damage in patients affected by systemic inflammatory response or sepsis

Detection and characterization of classical and &quot;uncommon&quot; exon 19 Epidermal Growth Factor Receptor mutations in lung cancer by pyrosequencing

BACKGROUND: The management of advanced stage non-small cell lung cancer is increasingly based on diagnostic and predictive analyses performed mostly on limited amounts of tumor tissue. The evaluation of Epidermal Growth Factor Receptor (EGFR) mutations have emerged as the strongest predictor of response to EGFR-tyrosine kinase inhibitors mainly in patients with adenocarcinoma. Several EGFR mutation detection techniques are available, having both sensitivity and specificity issues, being the Sanger sequencing technique the reference standard, with the limitation of a relatively high amount of mutated cells needed for the analysis. METHODS: A novel nucleotide dispensation order for pyrosequencing was established allowing the identification and characterization of EGFR mutation not definable with commercially and clinically approved kits, and validated in a consecutive series of 321 lung cancer patients (246 biopsies or cytology samples and 75 surgical specimens). RESULTS: 61/321 (19%) mutated cases were detected, 17 (27.9%) in exon 21 and 44 (72.1%) in exon 19, these latter corresponding to 32/44 (72.7%) classical and 12/44 (27.3%) uncommon mutations. Furthermore, a novel, never reported, point mutation, was found, which determined a premature stop codon in the aminoacidic sequence that resulted in a truncated protein in the tyrosine kinase domain, thus impairing the inhibitory effect of specific therapy. CONCLUSIONS: The novel dispensation order allows to detect and characterize both classical and uncommon EGFR mutations. Although several phase III studies in genotypically defined groups of patients are already available, further prospective studies assessing the role of uncommon EGFR mutations are warranted

Using partial triadic analysis for depicting the temporal evolution of Italian private healthcare organizations

The economic-financial configuration of Italian private hospitals is little explored, together with the governance and strategic structures. The aim of this work is to bridge this with the help of a statistical-quantitative method, analyzing the evolution of the configurations of Italian private hospital. Methodologically, after having collected the balance sheet data of all the Italian RSAs and having built a dataset with the data of 2008, 2012 and 2016, a factor analysis (PTA) was combined with clustering techniques to trace the profile of the Italian Private Hospitals in their evolution from the beginning of the Return Plans at the end of their third three-year period. The work concludes with a methodological proposal for the use of statistical analyzes useful for the domain of accounting and budget data

Financial configurations of Italian private hospitals: an evolutionary analysis

Private hospitals are an important pillar in many hybrid systems. In Italy they are bound to grow, but we have little knowledge of how they are coping with financial pressures. We use a configurational approach to determine the relationship between the macroprofiles of Italian private hospitals and their performance. We built a unique dataset with governance and financial statements data of all Italian private hospitals. We use a combination of partial triadic analysis (PTA) and clustering technique to identify both the main explicative financial dimensions and hospital configurations, and trace their evolutionary paths from the beginning of Regional Health Care Turnaround Plans (2008) to 2016. Understanding the evolution of configurations, our study entails also some implications for policy and practice