Review
Medicine, General & Internal
Vanesa Pereira-Prado, Felipe Martins-Silveira, Estafania Sicco, Jimena Hochmann, Mario Alberto Isiordia-Espinoza, Rogelio Gonzalez Gonzalez, Deepak Pandiar, Ronell Bologna-Molina
Summary: Differential diagnosis and prognosis of head and neck tumors have always been challenging due to their similarities and complexity. Artificial intelligence applications in digital histopathological image analysis have shown to be helpful in the objective interpretation of oral squamous cell carcinoma. Further research is necessary, especially in terms of clinical validation.
Article
Oncology
Yasaman Fatapour, Arash Abiri, Edward C. C. Kuan, James P. P. Brody
Summary: Despite diagnostic advancements, reliable prognostic systems for cancer recurrence risk assessment remain challenging. A novel framework was developed in this study to generate representative machine-learning prediction models for oral tongue squamous cell carcinoma (OTSCC) recurrence. The Gradient Boosting Machine model performed the best, achieving high accuracy and precision in predicting 5- and 10-year recurrence. Factors such as prior tumors, patient age, site of recurrence, and tumor histology were identified as significant predictors. The implementation of this framework demonstrates its potential for building generalizable screening tools for predicting tumor recurrence in various cancers.
Article
Chemistry, Analytical
Atta-ur Rahman, Abdullah Alqahtani, Nahier Aldhafferi, Muhammad Umar Nasir, Muhammad Farhan Khan, Muhammad Adnan Khan, Amir Mosavi
Summary: Oral cancer is a dangerous and common cancer, traditional microscopic biopsy image detection methods have limitations, and there is a high possibility of human error. With the development of technology, deep learning algorithms play an increasingly important role in the field of oral cancer image diagnosis, improving classification accuracy.
Article
Biochemistry & Molecular Biology
Hwa-Yen Chiu, Rita Huan-Ting Peng, Yi-Chian Lin, Ting-Wei Wang, Ya-Xuan Yang, Ying-Ying Chen, Mei-Han Wu, Tsu-Hui Shiao, Heng-Sheng Chao, Yuh-Min Chen, Yu-Te Wu
Summary: This study presents a machine learning method for early lung cancer detection using chest X-rays and demonstrates its effectiveness in assisting radiologists in the early detection of lung nodules.
Review
Oncology
Ibrahim Elmakaty, Mohamed Elmarasi, Ahmed Amarah, Ruba Abdo, Mohammed Imad Malki
Summary: Early and accurate diagnosis of oral squamous cell carcinoma (OSCC) is crucial for improving prognosis. This meta-analysis evaluated the accuracy of artificial intelligence (AI)-assisted technologies in detecting OSCC and found that AI-assisted systems have the potential to detect OSCC with high accuracy, aiding in early diagnosis.
CRITICAL REVIEWS IN ONCOLOGY HEMATOLOGY
(2022)
Article
Agriculture, Dairy & Animal Science
V. A. Teixeira, A. M. Q. Lana, T. Bresolin, T. R. Tomich, G. M. Souza, J. Furlong, J. P. P. Rodrigues, S. G. Coelho, L. C. Goncalves, J. A. G. Silveira, L. D. Ferreira, E. J. Facury Filho, M. M. Campos, J. R. R. Dorea, L. G. R. Perira
Summary: Bovine anaplasmosis causes significant economic losses in dairy cattle production systems worldwide, and conventional detection methods are laborious and costly. This study explores the early identification of anaplasmosis using wearable sensors and recurrent neural networks. The findings suggest a great potential for wearable sensors in early detection of anaplasmosis diseases.
JOURNAL OF DAIRY SCIENCE
(2022)
Review
Biochemistry & Molecular Biology
Nausheen Khanam, Rajnish Kumar
Summary: Artificial intelligence (AI) has great potential in early cancer detection by improving prediction models' accuracy using machine learning and deep learning techniques, assisting in the diagnosis of common cancers such as breast, lung, brain, and skin.
CURRENT MEDICINAL CHEMISTRY
(2022)
Article
Oncology
Li-Yu Lee, Cheng-Han Yang, Yu-Chieh Lin, Yu-Han Hsieh, Yung-An Chen, Margaret Dah-Tsyr Chang, Yen-Yin Lin, Chun-Ta Liao
Summary: The study developed a deep learning-based human-enhanced tool, called Domain-KEY algorithm, for identifying perineural invasion (PNI) in digital slides. The algorithm was able to accurately detect PNI in patients with oral cavity squamous cell carcinoma (OCSCC) and provide rapid diagnostic results.
FRONTIERS IN ONCOLOGY
(2022)
Review
Oncology
Maria Garcia-Pola, Eduardo Pons-Fuster, Carlota Suarez-Fernandez, Juan Seoane-Romero, Amparo Romero-Mendez, Pia Lopez-Jornet
Summary: The scoping review analyzed the use of artificial intelligence in oral cancer screening and found that AI tools can contribute to the early diagnosis of oral cancer, but improvements are still needed.
Article
Medicine, General & Internal
Daniele Roberto Giacobbe, Alessio Signori, Filippo Del Puente, Sara Mora, Luca Carmisciano, Federica Briano, Antonio Vena, Lorenzo Ball, Chiara Robba, Paolo Pelosi, Mauro Giacomini, Matteo Bassetti
Summary: Sepsis is a major cause of death worldwide, and the use of machine learning models for predicting clinically relevant events has garnered attention. Despite important pitfalls, the increasing involvement of artificial intelligence and machine learning in healthcare is undeniable. Rigorous multidisciplinary approaches are needed to enrich our understanding and enhance medical decision-making in the application of machine learning techniques for early recognition of sepsis.
FRONTIERS IN MEDICINE
(2021)
Article
Dentistry, Oral Surgery & Medicine
S. Y. Yang, S. H. Li, J. L. Liu, X. Q. Sun, Y. Y. Cen, R. Y. Ren, S. C. Ying, Y. Chen, Z. H. Zhao, W. Liao
Summary: This study developed a deep learning model to assist pathologists in diagnosing oral squamous cell carcinoma (OSCC), demonstrating improved diagnostic accuracy and speed in both junior and senior pathologists.
JOURNAL OF DENTAL RESEARCH
(2022)
Article
Dentistry, Oral Surgery & Medicine
Wei Yuan, Jinsuo Yang, Boya Yin, Xingyu Fan, Jing Yang, Haibin Sun, Yanbin Liu, Ming Su, Sen Li, Xin Huang
Summary: This study presents a novel Multi-Level Deep Residual Learning (MDRL) network to identify malignant and benign tissues from Optical Coherence Tomography (OCT) images. The MDRL system achieves excellent diagnostic performance in both image-level and resected patch-level, outperforming traditional CNNs and a specialist.
Article
Oncology
Muhammad Shaban, Shan E. Ahmed Raza, Mariam Hassan, Arif Jamshed, Sajid Mushtaq, Asif Loya, Nikolaos Batis, Jill Brooks, Paul Nankivell, Neil Sharma, Max Robinson, Hisham Mehanna, Syed Ali Khurram, Nasir Rajpoot
Summary: This study investigated the prognostic significance of tumour-associated stroma infiltrating lymphocytes in head and neck squamous cell carcinoma using an AI-based automated method. The TASIL-score was found to be predictive of disease-specific survival and showed better separation between low- and high-risk patients compared to manual TILs scoring. Positive correlation with CD8(+) T cell estimates was also observed. Further validation on larger multicentric cohorts is necessary before clinical adoption.
JOURNAL OF PATHOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Tao Zhou, Jian Guan, Bao Feng, Huimin Xue, Jin Cui, Qionglian Kuang, Yehang Chen, Kuncai Xu, Fan Lin, Enming Cui, Wansheng Long
Summary: This study developed a machine learning model based on CT images to differentiate benign renal tumors from renal cell carcinomas (RCCs) and improve radiologists' diagnostic performance. The results showed that the ML model based on 3D images performed better than that based on 2D images, with the highest AUC of 0.81 and accuracy of 0.86. Radiologists achieved better performance by referring to the classifier's decision.
EUROPEAN RADIOLOGY
(2023)
Article
Medicine, General & Internal
Debdipto Misra, Venkatesh Avula, Donna M. Wolk, Hosam A. Farag, Jiang Li, Yatin B. Mehta, Ranjeet Sandhu, Bipin Karunakaran, Shravan Kethireddy, Ramin Zand, Vida Abedi
Summary: This study developed a clinical decision support system to predict the progression to septic shock in patients up to 6 hours from the time of admission. The results indicated that defining sepsis based on clinical variables outperformed definitions based solely on billing information.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Dentistry, Oral Surgery & Medicine
K. Ankita, V. Shwetha, S. Vanitha, S. Reddy Sujatha, R. Nagaraju, K. Tupakula Pavan
JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY
(2019)
Letter
Oncology
Ankita Kar, Shalini Thakur, Vishal U. S. Rao
Letter
Oncology
Ankita Kar, Adegbola Adeniji, Vishal U. S. Rao, Mithua Ghosh
Letter
Oncology
Shaswata Karmakar, Ankita Kar, Shalini Thakur, Vishal U. S. Rao
Review
Dentistry, Oral Surgery & Medicine
Uchilla S. Vishal Rao, Gururaj Arakeri, Sambhavi Ravishankar, Ankita Kar, Shalini Thakur, Ryan J. Li, K. Dhananjay, Tejaswi Surya, Pankaj Chaturvedi, Ricardo S. Gomez, Peter A. Brennan
JOURNAL OF ORAL PATHOLOGY & MEDICINE
(2020)
Letter
Surgery
Ankita Kar, Anand Subash, Vishal U. S. Rao
Letter
Oncology
Ankita Kar, M. R. Asheem, Udayan Bhaumik, Vishal U. S. Rao
Letter
Psychiatry
Ankita Kar, Nirmalendu Saha, Asheem Ramiz, Udayan Bhaumik, C. Satish
MINERVA PSYCHIATRY
(2021)
