Management accounting change in merger and acquisitions: a multiple-case study

Autor: Mariani, Andrea, Cifalinò, Antonella, Lisi, Irene Eleonora, Rizzo, Marco Giovanni

Publikováno v: Journal of Accounting & Organizational Change, 2024, Vol. 20, Issue 6, pp. 252-276.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/JAOC-01-2024-0004

Uncertainty-aware Self-supervised Learning for Cross-domain Technical Skill Assessment in Robot-assisted Surgery

Autor: Wang, Ziheng, Mariani, Andrea, Menciassi, Arianna, De Momi, Elena, Fey, Ann Majewicz

Objective technical skill assessment is crucial for effective training of new surgeons in robot-assisted surgery. With advancements in surgical training programs in both physical and virtual environments, it is imperative to develop generalizable met

Externí odkaz: http://arxiv.org/abs/2304.14589

Evaluating nutrition in advanced ovarian cancer: which biomarker works best?

Autor: Fumagalli, Diletta, Sonik, Roma, De Vitis, Luigi A., Rossi, Valentina, Bazzurini, Luca, McGree, Michaela E., Fought, Angela J., Mariani, Andrea, Cliby, William A., Kumar, Amanika

Publikováno v: In Gynecologic Oncology September 2024 188:97-102

Clinical research in endometrial cancer: consensus recommendations from the Gynecologic Cancer InterGroup

Autor: Barretina-Ginesta, Pilar, Bennett, Katherine, Berek, Jonathan, Berger, Regina, Bjørge, Line, Boere, Ingrid, Brennan, Donal, Bruchim, Ilan, Chang, Ting-Chang, Chavez Blanco, Adriana, Chen, Xiaojun, Colombo, Nicoletta, Crosbie, Emma, Denys, Hannelore, Duska, Linda, Fruehauf, Filip, Gomez Garcia, Eva Maria, van Gorp, Toon, Grimm, Christoph, Guitmann, Gustavo, Han, Kathy, Hanker, Lars, Harano, Kenichi, Hasegawa, Kosei, Herrington, C Simon, Ip, Philip, Joly, Florence, Khaw, Pearly, Kohn, Elise, Kristeleit, Rebecca, Kroep, Judith, Leary, Alexandra, Lee, Jung-Yun, Lheureux, Stephanie, Liu, Jihong, Mackay, Helen, Mahner, Sven, Mariani, Andrea, McAlpine, Jessica, Mikami, Yoshiki, Mirza, Mansoor Raza, Mukhopadhyay, Asima, Nagao, Shoji, Ng, Joseph, Nogueira-Rodrigues, Angelica, Novák, Zoltán, O'Donnell, Jennifer, Osborne, Sherill, Perez-Fidalgo, J. Alejandro, Romeo Marin, Margarita, Roy Chowdhury, Rahul, Sadozye, Azmat, Safra, Tamar, Scott, Claire, Sehouli, Jalid, Slomovitz, Brian, Tan, David, Taylor, Alexandra, Valabrega, Giorgio, Veneziani, Ana, Verhoeven, Karen, Vetter, Marcus, Wampfler, Julian, Westin, Shannon, Wimberger, Pauline, Zola, Paolo, Creutzberg, Carien L ^{*, *}, Kim, Jae-Weon ^*, Eminowicz, Gemma, Allanson, Emma, Eberst, Lauriane, Kim, Se Ik, Nout, Remi A, Park, Jeong-Yeol, Lorusso, Domenica, Mileshkin, Linda, Ottevanger, Petronella B, Brand, Alison, Mezzanzanica, Delia, Oza, Amit, Gebski, Val, Pothuri, Bhavana, Batley, Tania ^†, Gordon, Carol ^†, Mitra, Tina ^†, White, Helen ^†, Howitt, Brooke, Matias-Guiu, Xavier, Ray-Coquard, Isabelle, Gaffney, David, Small, William, Jr, Miller, Austin, Concin, Nicole, Powell, Matthew A, Stuart, Gavin, Bookman, Michael A

Publikováno v: In The Lancet Oncology September 2024 25(9):e420-e431

A surgical dataset from the da Vinci Research Kit for task automation and recognition

Autor: Rivas-Blanco, Irene, Pérez-del-Pulgar, Carlos J., Mariani, Andrea, Tortora, Giuseppe, Reina, Antonio J.

The use of datasets is getting more relevance in surgical robotics since they can be used to recognise and automate tasks. Also, this allows to use common datasets to compare different algorithms and methods. The objective of this work is to provide

Externí odkaz: http://arxiv.org/abs/2102.03643