Article
Oncology
Vincenza Granata, Roberta Fusco, Federica De Muzio, Carmen Cutolo, Sergio Venanzio Setola, Federica Dell'Aversana, Alessandro Ottaiano, Guglielmo Nasti, Roberta Grassi, Vincenzo Pilone, Vittorio Miele, Maria Chiara Brunese, Fabiana Tatangelo, Francesco Izzo, Antonella Petrillo
Summary: This study aimed to evaluate the effectiveness of radiomics features obtained by EOB-MRI phase in predicting clinical outcomes and assessing various factors in patients with colorectal liver metastases. The results showed that radiomics can serve as biomarkers to identify prognostic features that may influence treatment choices in these patients.
Article
Gastroenterology & Hepatology
Kevin A. Chen, Chinmaya U. Joisa, Karyn B. Stitzenberg, Jonathan Stem, Jose G. Guillem, Shawn M. Gomez, Muneera R. Kapadia
Summary: Machine learning approaches have shown superiority in predicting readmission after colorectal surgery compared to traditional statistical methods.
JOURNAL OF GASTROINTESTINAL SURGERY
(2022)
Article
Surgery
Jeongyoon Moon, Allison Pang, Gabriela Ghitulescu, Julio Faria, Nancy Morin, Carol-Ann Vasilevsky, Marylise Boutros
Summary: Early post-operative discharge of colorectal cancer patients is increasing without improvement in readmission rates and an overall increase in hospitalization costs. Premature discharge of select patients may result in readmissions, leading to increased resource utilization.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2022)
Article
Surgery
Caitlin Stafford, Todd Francone, Patricia L. Roberts, Peter W. Marcello, Rocco Ricciardi
Summary: The study found that patients who were converted to open surgery had a higher morbidity rate compared to those who underwent completed laparoscopic surgery. However, the overall morbidity rate of the converted procedures was still lower than open surgery. Importantly, the additional morbidity of converted procedures appears to be related to the risk of surgical site infection.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2021)
Article
Computer Science, Artificial Intelligence
Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek
Summary: Explainable Artificial Intelligence (XAI) is a research field that aims to bring transparency to complex and opaque machine learning models. This paper provides an overview of techniques that practically apply XAI to improve ML models, categorizing and comparing their strengths and weaknesses. Theoretical perspectives and empirical experiments demonstrate how explanations can enhance properties such as model generalization and reasoning. The potential caveats and drawbacks of these methods are also discussed.
INFORMATION FUSION
(2023)
Article
Multidisciplinary Sciences
Joel D'Souza, Timothy Eglinton, Frank Frizelle
Summary: This study aimed to define the rate of unplanned readmissions within 30 days after colorectal cancer surgery, identify risk factors, and develop a predictive model. The study found that postoperative complications, stoma formation, high-grade complications, and rectal cancer were significant risk factors for unplanned readmissions. Targeted outpatient follow-up within two weeks of discharge with appropriate surgical expertise is the most effective strategy for preventing readmissions.
Article
Surgery
Mohamed A. Abd El Aziz, William R. G. Perry, Fabian Grass, Amit Merchea, Laura E. Raffals, Kellie L. Mathis, Kevin T. Behm
Summary: Limited literature on the impact of the extent of resection on short-term outcomes in elective surgery for UC. The operative approach has a greater impact on short-term outcomes and length of stay than the extent of resection. Laparoscopic TPC has a higher rate of prolonged length of stay compared to laparoscopic STC.
UPDATES IN SURGERY
(2021)
Article
Surgery
Joseph R. Nellis, Zhifei Sun, Bora Chang, Gina Della Porta, Christopher R. Mantyh
Summary: This study evaluated whether real-time knowledge of patients' risk status paired with a stratified intervention was associated with a reduction in acute kidney injury and 30-day readmission following colorectal surgery. The results showed that utilization of the risk-based management platform was associated with a 2.5% decrease in the rate of acute kidney injury and a 3.1% decrease in the rate of readmissions.
JOURNAL OF SURGICAL RESEARCH
(2023)
Article
Multidisciplinary Sciences
Alessandro Boaro, Jakub R. Kaczmarzyk, Vasileios K. Kavouridis, Maya Harary, Marco Mammi, Hassan Dawood, Alice Shea, Elise Y. Cho, Parikshit Juvekar, Thomas Noh, Aakanksha Rana, Satrajit Ghosh, Omar Arnaout
Summary: Accurate segmentation and volumetric assessment of brain meningiomas are crucial for clinical practice. Fully-automated algorithms can improve accuracy, efficiency, and reduce inter-user variability. Previous research mainly focused on segmentation tasks and lacked evaluation of deep learning solutions in clinical practice.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Cowan Ho, Zitong Zhao, Xiu Fen Chen, Jan Sauer, Sahil Ajit Saraf, Rajasa Jialdasani, Kaveh Taghipour, Aneesh Sathe, Li-Yan Khor, Kiat-Hon Lim, Wei-Qiang Leow
Summary: Colorectal cancer is one of the most common cancers worldwide. Researchers have developed a unique artificial intelligence deep learning model to assist in screening for malignant tumors in colorectal specimens, improving cancer detection and classification, and alleviating the workload of pathologists. The model demonstrates high sensitivity and can accurately identify high-risk colorectal features.
SCIENTIFIC REPORTS
(2022)
Article
Health Care Sciences & Services
Kim Huat Goh, Le Wang, Adrian Yong Kwang Yeow, Yew Yoong Ding, Lydia Shu Yi Au, Hermione Mei Niang Poh, Ke Li, Joannas Jie Lin Yeow, Gamaliel Yu Heng Tan
Summary: This study utilized text-mining techniques to identify psychosocial factors from EMR clinical notes and found that these factors significantly improved the accuracy of predicting hospital readmission risk among older adults. The results suggest the feasibility and value of extracting psychosocial information from clinical notes for improving readmission risk prediction.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Gastroenterology & Hepatology
Jessica Bogach, Gregory Pond, Cagla Eskicioglu, Marko Simunovic, Hsien Seow
Summary: In patients with IBD-associated CRC, segmental resection and proctocolectomy are associated with similar survival outcomes in both UC and CD patients, while total colectomy is linked to worse survival. Prospective studies are needed to further explore these findings.
JOURNAL OF GASTROINTESTINAL SURGERY
(2021)
Review
Oncology
Sergei Bedrikovetski, Nagendra N. Dudi-Venkata, Hidde M. Kroon, Warren Seow, Ryash Vather, Gustavo Carneiro, James W. Moore, Tarik Sammour
Summary: The systematic review found that AI models have higher accuracy in predicting lymph node metastasis in rectal and colorectal cancer, especially when using deep learning models. There is significant heterogeneity among radiomics studies, and there is still a lack of research in the field of deep learning.
Article
Surgery
Milan Patel, Mahfuzul Haque, Divyanshoo Kohli, Pritesh Mutha, Syed A. Shah, Leopoldo Fernandez, Alvin Zfass, Tilak Shah
Summary: This study showed high success rates of endoscopic resection in veterans with colorectal polyps >= 2 cm and >= 4 cm, with lower rates of serious complications compared to surgical resection. Choosing endoscopic resection as the initial treatment strategy reduced morbidity compared to laparoscopic surgery, especially for polyps >= 4 cm.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2021)
Article
Surgery
Omeed Moaven, Thomas E. Tavolara, Cristian D. Valenzuela, Tan To Cheung, Carlos U. Corvera, Charles H. Cha, John A. Stauffer, Muhammad Khalid Khan Niazi, Metin N. Gurcan, Perry Shen
Summary: Machine learning models have been developed to predict survival and recurrence after surgery for colorectal liver metastases. The models showed good predictive power, with the gradient-boosted trees model performing better. These models have the potential to be adopted in clinical practice.
JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS
(2023)
Article
Multidisciplinary Sciences
Bridget M. Nugent, Carly M. O'Donnell, C. Neill Epperson, Tracy L. Bale
NATURE COMMUNICATIONS
(2018)
Article
Cell Biology
Erica B. Baller, Alessandra M. Valcarcel, Azeez Adebimpe, Aaron Alexander-Bloch, Zaixu Cui, Ruben C. Gur, Raquel E. Gur, Bart L. Larsen, Kristin A. Linn, Carly M. O'Donnell, Adam R. Pines, Armin Raznahan, David R. Roalf, Valerie J. Sydnor, Tinashe M. Tapera, M. Dylan Tisdall, Simon Vandekar, Cedric H. Xia, John A. Detre, Russell T. Shinohara, Theodore D. Satterthwaite
Summary: We explore the relationship between cerebral blood flow (CBF) and the amplitude of low-frequency fluctuations (ALFF), and find specific changes in coupling over age, which are related to biological sex and executive function. This highlights the importance of CBF-ALFF coupling throughout development and its potential as a target for studying neuropsychiatric diseases.
Article
Radiology, Nuclear Medicine & Medical Imaging
Lynn Daboul, Carly M. O'Donnell, Quy Cao, Moein Amin, Paulo Rodrigues, John Derbyshire, Christina Azevedo, Amit Bar-Or, Eduardo Caverzasi, Peter Calabresi, Bruce A. C. Cree, Leorah Freeman, Roland G. Henry, Erin E. Longbrake, Kunio Nakamura, Jiwon Oh, Nico Papinutto, Daniel Pelletier, Rohini D. Samudralwar, Suradech Suthiphosuwan, Matthew K. Schindler, Elias S. Sotirchos, Nancy L. Sicotte, Andrew J. Solomon, Russell T. Shinohara, Daniel S. Reich, Daniel Ontaneda, Pascal Sati
Summary: This study assesses the impact of gadolinium-based contrast agent (GBCA) on the evaluation of central vein sign (CVS) and the diagnostic performance of CVS for multiple sclerosis (MS). The results show that the use of GBCA enhances the detection rate of CVS on FLAIR* images and improves the sensitivity of CVS for the diagnosis of MS.
AMERICAN JOURNAL OF ROENTGENOLOGY
(2023)
Article
Neurosciences
Carly M. O'Donnell, Sara J. J. Swanson, Chad E. E. Carlson, Manoj Raghavan, Peter A. A. Pahapill, Christopher Todd Anderson
Summary: This study explores the use of responsive thalamic stimulation in patients with drug-resistant genetic generalized epilepsies (GGEs). The results show significant improvement in seizure control for two patients and seizure freedom for one patient. These findings suggest that responsive thalamic stimulation may be an effective treatment option for GGEs.
Article
Clinical Neurology
Kelly M. Clark, Carly A. O'Donnell, Mark Elliott, Shahamat E. Tauhid, Blake Dewey, Renxin Chu, Samar Khalil, Govind Nair, Pascal Sati, Anna DuVal, Nicole Pellegrini, Amit Bar-Or, Clyde K. Markowitz, Matthew Schindler, Jonathan A. Zurawski, Peter S. Calabresi, Daniel Reich, Rohit T. Bakshi, Russell Shinohara, NAIMS Cooperative
Summary: This study aimed to assess the biases in image-based measures due to scanner or site differences in multicenter studies. The results showed that despite protocol harmonization, differences in brain volumetry persist across MR scanners.
JOURNAL OF NEUROIMAGING
(2023)
Meeting Abstract
Neurosciences
Erica Baller, Alessandra Valcarel, Azeez Adebimpe, Aaron Alexander-Bloch, Zaixu Cui, Ruben Gur, Raquel Gur, Bart Larsen, Kristin Linn, Carly O'Donnell, Adam Pines, Armin Raznahan, David Roalf, Valerie Sydnor, Tinashe M. Tapera, M. Dylan Tisdall, Simon Vandekar, Cedric Huchuan Xia, John Detre, Russell Shinohara, Theodore Satterthwaite
BIOLOGICAL PSYCHIATRY
(2022)