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Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry

Emad A. Rakha, Konstantinos Vougas, Puay Hoon Tan
2021 Pathobiology (Basel)  
Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades.  ...  The use of AI tools in breast pathology is discussed briefly as it is covered in other reviews. Here, we present the main application of digital technology in IHC.  ...  Digital technology tools have been used in pathol- Digital technology has been used in the field of diagnostic ogy for many years and examples include computers, breast pathology and  ... 
doi:10.1159/000521149 pmid:34969036 fatcat:rx4rloc5vzch5cc2b7tlqcfxkq

Mining Inter-Relationships in Online Scientific Articles and its Visualization: Natural Language Processing for Systems Biology Modeling

Nidheesh Melethadathil, Jaap Heringa, Bipin Nair, Shyam Diwakar
2019 International Journal of Online and Biomedical Engineering (iJOE)  
Compared to normal clustering, auto-clustering demonstrated better efficacy by generating larger numbers of unique and relevant cluster labels.  ...  The efficacy of this document clustering and visualization platform was evaluated by expert-based validation of clustering results obtained with unique search terms.  ...  , Sanu Shaji for his help in evaluating the cluster results and Hemalatha Sasidharakurup for her test case evaluation.  ... 
doi:10.3991/ijoe.v15i02.9432 fatcat:ugd6jo3mbfcq5ewfekt3p2plye

Computational Pathology Definitions, Best Practices, and Recommendations for Regulatory Guidance: A White Paper from the Digital Pathology Association

Esther Abels, Liron Pantanowitz, Famke Aeffner, Mark D. Zarella, Jeroen vd Laak, Marilyn M. Bui, Venkata N. P. Vemuri, Anil V. Parwani, Jeff Gibbs, Emmanuel Agosto‐Arroyo, Andrew H. Beck, Cleopatra Kozlowski
2019 Journal of Pathology  
Best practices for implementing computational pathology workflows are presented.  ...  Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors.  ...  Acknowledgements We would like to thank Joel Saltz for expert review of the manuscript, and Navid Farahani, Katherine Scott, and Hunter Jackson for helpful discussions.  ... 
doi:10.1002/path.5331 pmid:31355445 pmcid:PMC6852275 fatcat:mjuwxeczbbcibc75pxkyg5w3wy

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer

Philip M.P. Poortmans, Silvia Takanen, Gustavo Nader Marta, Icro Meattini, Orit Kaidar-Person
2019 Breast  
Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing  ...  An infinite gradient of volumes and doses to deliver spatially-adjusted radiation can be generated, allowing to avoid unnecessary radiation to organs at risk.  ...  automatic segmentation, deformable registration, response-adaptive clinical decision-making, refined imaging generation tools, and toxicity prediction models [84e89].  ... 
doi:10.1016/j.breast.2019.11.011 pmid:31931265 pmcid:PMC7375562 fatcat:ybzauszfabaipar2f4icpmork4

Machine-Learning-Based Diagnostics of EEG Pathology

Lukas A.W. Gemein, Robin T. Schirrmeister, Patryk Chrabąszcz, Daniel Wilson, Joschka Boedecker, Andreas Schulze-Bonhage, Frank Hutter, Tonio Ball
2020 NeuroImage  
We make the proposed feature-based framework available open source and thus offer a new tool for EEG machine learning research.  ...  Machine learning (ML) methods have the potential to automate clinical EEG analysis.  ...  This does not only hold for EEG pathology decoding tasks, but also for EEG decoding tasks in general.  ... 
doi:10.1016/j.neuroimage.2020.117021 pmid:32534126 fatcat:g254z7bjc5cevmy76kzb3tvho4

A New Metric for Detecting Change in Slowly Evolving Brain Tumors: Validation in Meningioma Patients

Kilian M Pohl, Ender Konukoglu, Sebastian Novellas, Nicholas Ayache, Andriy Fedorov, Ion-Florin Talos, Alexandra Golby, William M Wells, Ron Kikinis, Peter M Black
2011 Operative Neurosurgery  
Measurements based on experts' segmentation are highly accurate but generally too labor intensive for standard clinical settings.  ...  BACKGROUND: Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies.  ...  Finally, the 3 measurements varied by almost 1 mL or 6% in volume, which is quite large given that the measured change in pathology for each of the 9 patients with serial imaging was less than 1 mL.  ... 
doi:10.1227/neu.0b013e31820783d5 pmid:21206318 pmcid:PMC3099129 fatcat:ok465nkb7bdsxg6ukhw3iq3m4a

Machine-Learning-Based Diagnostics of EEG Pathology [article]

Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabąszcz, Daniel Wilson, Joschka Boedecker, Andreas Schulze-Bonhage, Frank Hutter, Tonio Ball
2020 arXiv   pre-print
We make the proposed feature-based framework available open source and thus offer a new tool for EEG machine learning research.  ...  Machine learning (ML) methods have the potential to automate clinical EEG analysis.  ...  Code specific to the experiments performed for our study was uploaded to github.com/gemeinl/auto-eeg-diagnosis-comparison.  ... 
arXiv:2002.05115v1 fatcat:hquq4wvkfref7amyzvi6uupmxq

CIDI-lung-seg: A single-click annotation tool for automatic delineation of lungs from CT scans

Awais Mansoor, Ulas Bagci, Brent Foster, Ziyue Xu, Deborah Douglas, Jeffrey M. Solomon, Jayaram K. Udupa, Daniel J. Mollura
2014 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
Accurate and fast extraction of lung volumes from computed tomography (CT) scans remains in a great demand in the clinical environment because the available methods fail to provide a generic solution due  ...  This paper presents a lung annotation tool for CT images that is interactive, efficient, and robust.  ...  With the increased exposure of computer-assisted diagnosis methods, automated analysis tools are often sought for quick and accurate diagnosis and quantification [2] , [3] .  ... 
doi:10.1109/embc.2014.6943783 pmid:25570151 pmcid:PMC5537720 dblp:conf/embc/MansoorBFXDSUM14 fatcat:terwiojbtbfwzdkkplnkv47xry

Near-infrared auto-fluorescence spectroscopy combining with Fisher's linear discriminant analysis improves intraoperative real-time identification of normal parathyroid in thyroidectomy

Junsong Liu, Xiaoxia Wang, Rui Wang, Chongwen Xu, Ruimin Zhao, Honghui Li, Shaoqiang Zhang, Xiaobao Yao
2020 BMC Surgery  
To evaluate the efficacy of a sensitive, real-time tool for identification and protection for parathyroid glands during thyroidectomy.  ...  Accuracy was evaluated by comparison with histology and NIR identification. Data were attracted for Fisher's linear discriminant analysis.  ...  We thank them for their generous help.  ... 
doi:10.1186/s12893-019-0670-x pmid:31907042 pmcid:PMC6945439 fatcat:72dpz57v5zg5tgdbvnabcsinze

BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework

Newton Howard, Naima Chouikhi, Ahsan Adeel, Katelyn Dial, Adam Howard, Amir Hussain
2020 Frontiers in Computational Neuroscience  
This is based on the assumption that principles by which the brain seemingly operate, to the extent that it can be understood as computational, should at least be tested as principles for the operation  ...  Computational approaches to the cognitive sciences and to neuroscience are partly premised on the idea that computational simulations of such cognitive functions and brain operations suspected to correspond  ...  framework, which are cited here for reference.  ... 
doi:10.3389/fncom.2020.00016 pmid:32194389 pmcid:PMC7063840 fatcat:4czu2v4eurgrxibvqbuht355bq

Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?

Alex Zhavoronkov, Quentin Vanhaelen, Tudor I. Oprea
2020 Clinical Pharmacology and Therapeutics  
We address difficulties and AI/ML developments for target identification, their use in generative chemistry for small molecule drug discovery, and the potential role of AI/ML in clinical trial outcome  ...  evaluation.  ...  under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for  ... 
doi:10.1002/cpt.1795 pmid:31957003 pmcid:PMC7158211 fatcat:dtowooen6fhwvhnnew2e75nify

Bone Strain Index predicts fragility fracture in osteoporotic women: an artificial intelligence-based study

Fabio Massimo Ulivieri, Luca Rinaudo, Carmelo Messina, Luca Petruccio Piodi, Davide Capra, Barbara Lupi, Camilla Meneguzzo, Luca Maria Sconfienza, Francesco Sardanelli, Andrea Giustina, Enzo Grossi
2021 European Radiology Experimental  
For group comparisons, an independent-samples t-test was used; variables were expressed as mean ± standard deviation. Results For each patient, we evaluated a total of n = 6 exams.  ...  All subjects performed a spine x-ray to assess VFs, together with lumbar and femoral DXA for bone mineral density (BMD) and the bone strain index (BSI) evaluation.  ...  Mohammad Rafay Malik for the English language editing and review.  ... 
doi:10.1186/s41747-021-00242-0 pmid:34664136 pmcid:PMC8523735 fatcat:vnutaivglvaydoyukoovj4fx2a

Role of Q-Waves ECG in Myocardial Scar Assessment in patients with Prior Myocardial Infarction

Lucia PV, Anna LL, Catherine K, Tiziano M, Francesco FF
2019 Medical & Clinical Reviews  
Sensitivity and specificity of wallspecific ECG changes in presence of 2+ or 3+ pathological Q waves in the corresponding wall leads have been evaluated for anterior (V1-V4 leads), inferior (D2, DIII,  ...  The sensitivity and specificity of wall-specific ECG changes in presence of 2+ pathological Q-waves were 42% and 88% for anterior, 43% and 69.9% for inferior and 28.6% and 76% for lateral wall; in presence  ...  In particular the sensitivity and specificity of wall-specific ECG changes considering the presence of 2+ or 3+ pathological Q waves in the corresponding wall leads have been evaluated for anterior, inferior  ... 
doi:10.36648/2471-299x.5.2.79 fatcat:3zuivv5ffzhrtphfyeafd5bfye

EP-1886: The feasibility of atlas-based automatic segmentation of MRI for H&N radiotherapy planning

R. Speight, K. Wardman, M. Gooding, R. Preswich
2016 Radiotherapy and Oncology  
Purpose or Objective: Atlas-based autosegmentation is an established tool for segmenting structures for CT-planned head and neck radiotherapy.  ...  Based on the CT information two region of interest (ROI) were defined: Body (only extracranial region) and bone marrow "BM" (using auto-thresholding followed by manual exclusion of CT contrast agents).  ...  This fixed threshold does not account for potential differences between tissue types or for a variation of the perfusion component induced by a pathological condition.  ... 
doi:10.1016/s0167-8140(16)33137-1 fatcat:y3e6xfj6mrhjbayil53ti4kkuy

Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges

Maxwell A. Konnaris, Matthew Brendel, Mark Alan Fontana, Miguel Otero, Lionel B. Ivashkiv, Fei Wang, Richard D. Bell
2022 Arthritis Research & Therapy  
computational pathology approaches.  ...  for image analysis.  ...  Computational pathology and WSI have brought on a new era of computer-assisted analytical software [7] , and the development of novel computational tools for image analysis has highlighted the utility  ... 
doi:10.1186/s13075-021-02716-3 pmid:35277196 pmcid:PMC8915507 fatcat:s57bphpay5at7eqdklsh36bkim
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