Annotating for Artificial Intelligence Applications in Digital Pathology: A Practical Guide for Pathologists and Researchers

Montezuma, Diana; Oliveira, Sara P.; Neto, Pedro C.; Oliveira, Domingos Lucas Latorre de; Monteiro, Ana Raquel; Cardoso, Jaime S.; Macedo-Pinto, Isabel

doi:10.1016/j.modpat.2022.100086

Cited by 10 publications

(2 citation statements)

References 37 publications

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“…First, we note that a common approach to achieving large numbers of annotations consists simply of having more people making the annotations. Since it is difficult to find several expert pathologists who are available for the task, structured crowdsourcing is a possible approach, whereby people with less expertise make annotations in accordance with their level of skills, and their work is mentored and eventually corrected by expert pathologists [65,66].…”

Section: Optimize the Annotation Phase Timementioning

confidence: 99%

Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets

Fiorin,

López Pablo,

Lejeune

et al. 2024

J Digit Imaging. Inform. med.

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The field of immunology is fundamental to our understanding of the intricate dynamics of the tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment emerges as essential aspect in breast cancer cases. To gain comprehensive insights, the quantification of TILs through computer-assisted pathology (CAP) tools has become a prominent approach, employing advanced artificial intelligence models based on deep learning techniques. The successful recognition of TILs requires the models to be trained, a process that demands access to annotated datasets. Unfortunately, this task is hampered not only by the scarcity of such datasets, but also by the time-consuming nature of the annotation phase required to create them. Our review endeavors to examine publicly accessible datasets pertaining to the TIL domain and thereby become a valuable resource for the TIL community. The overall aim of the present review is thus to make it easier to train and validate current and upcoming CAP tools for TIL assessment by inspecting and evaluating existing publicly available online datasets.

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Section: Optimize the Annotation Phase Timementioning

confidence: 99%

Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets

Fiorin,

López Pablo,

Lejeune

et al. 2024

J Digit Imaging. Inform. med.

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“…The Internet and AI technology are two essential products in the information age. Since birth, they have created and realized many possibilities in various fields [9][10][11][12][13][14][15][16][17][18] . As an excellent tool to improve the concentration of college students, MR shooting games will produce tremendous superimposed efficiency under the blessing of Internet + AI technology and better serve college students 19 .…”

Section: The Stacking Empowerment Effect Of Mr Shooting Games and Ai ...mentioning

confidence: 99%

Concentration training of MR shooting game plus AI tech on college students

Liu,

Zhang,

2023

Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023)

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College students are the source of power for the country’s sustainable development, lack of concentration causes significant problem that leads to low learning acquisition for college students. The team uses literature, expert interviews, data statistics, and logical analysis to explore a solution that caters to college students’ preferences and has an above-notable concentration enhancement. Keeping close to the background of the times and fully integrating technological elements, the research is conducted on the inducing effect of MR shooting games on the concentration enhancement of college students. Comparing the experimental data, it is found that the MR shooting game has a more obvious intervention effect on the rehabilitation training and strengthening of the concentration of college students, and it and can be used as an effective tool for the induction of concentration enhancement of college students. At the same time, with the support of Internet+AI technology, it can have a subset considered enabling empowerment effect on MR shooting games, and realize self-iteration, migration, and the possibility of more functional expansion. It is helpful to support the improvement of concentration in more fields and the use and promotion of a vaster broader of work, and better serve the group of college students.

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Work-in-Progress: Immersive and Diversified Artificial Intelligence Education

Gao,

Srinivasan

2024

Lecture Notes in Networks and Systems

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Annotating for Artificial Intelligence Applications in Digital Pathology: A Practical Guide for Pathologists and Researchers

Cited by 10 publications

References 37 publications

Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets

Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets

Concentration training of MR shooting game plus AI tech on college students

Work-in-Progress: Immersive and Diversified Artificial Intelligence Education

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