| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Benedikt Feuerecker, Maurice M Heimer, Thomas Geyer, Matthias P Fabritius, Sijing Gu, Balthasar Schachtner, Leonie Beyer, Jens Ricke, Sergios Gatidis, Michael Ingrisch, Clemens C Cyra. Artificial Intelligence in Oncological Hybrid Imaging. Nuklearmedizin. Nuclear medicine. vol 62. issue 5. 2023-10-06. PMID:37802057. |
given the rapid developments in machine learning (ml) and deep learning (dl) methods, the role of ai will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes. |
2023-10-06 |
2023-10-15 |
Not clear |
| J H Jensha Haennah, C Seldev Christopher, G R Gnana Kin. Prediction of the COVID disease using lung CT images by Deep Learning algorithm: DETS-optimized Resnet 101 classifier. Frontiers in medicine. vol 10. 2023-09-25. PMID:37746067. |
a clinical decision-making system with predictive algorithms is needed to alleviate the pressure on healthcare systems via deep learning (dl) algorithms. |
2023-09-25 |
2023-10-07 |
Not clear |
| Fan Fan, Gang Wu, Yining Yang, Fu Liu, Yuli Qian, Qingmiao Yu, Hongqiang Ren, Jinju Gen. A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening. Environmental science & technology. 2023-09-25. PMID:37749748. |
however, the currently available dl model for screening ees lacks both a transparent decision-making process and effective applicability domain (ad) characterization, making the reliability of its prediction results uncertain and limiting its practical applications. |
2023-09-25 |
2023-10-07 |
Not clear |
| Inferrera Leandro, Borsatti Lorenzo, Miladinovic Aleksandar, Marangoni Dario, Giglio Rosa, Accardo Agostino, Tognetto Daniel. OCT-based deep-learning models for the identification of retinal key signs. Scientific reports. vol 13. issue 1. 2023-09-05. PMID:37670066. |
labelled oct images remain a challenge, but our approach reduces dataset creation time and shows dl models' potential to improve ocular pathology diagnosis and clinical decision-making. |
2023-09-05 |
2023-10-07 |
Not clear |
| Wenjie Fan, Jiaqi Zhang, Nan Wang, Jia Li, Li H. The Application of Deep Learning on CBCT in Dentistry. Diagnostics (Basel, Switzerland). vol 13. issue 12. 2023-06-28. PMID:37370951. |
dl models have the potential to be used clinically as medical decision-making aids. |
2023-06-28 |
2023-08-14 |
Not clear |
| Zun Zheng Ong, Youssef Sadek, Xiaoxuan Liu, Riaz Qureshi, Su-Hsun Liu, Tianjing Li, Viknesh Sounderajah, Hutan Ashrafian, Daniel Shu Wei Ting, Dalia G Said, Jodhbir S Mehta, Matthew J Burton, Harminder Singh Dua, Darren Shu Jeng Tin. Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol. BMJ open. vol 13. issue 5. 2023-05-10. PMID:37164459. |
in recent years, deep learning (dl), a subfield of artificial intelligence, has rapidly emerged as a promising tool in assisting automated medical diagnosis, clinical triage and decision-making, and improving workflow efficiency in healthcare services. |
2023-05-10 |
2023-08-14 |
Not clear |
| Akhilanand Chaurasia, Arunkumar Namachivayam, Revan Birke Koca-Ünsal, Jae-Hong Le. Deep-learning performance in identifying and classifying dental implant systems from dental imaging: a systematic review and meta-analysis. Journal of periodontal & implant science. 2023-05-08. PMID:37154107. |
therefore, dl models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice. |
2023-05-08 |
2023-08-14 |
Not clear |
| Geemi P Wellawatte, Heta A Gandhi, Aditi Seshadri, Andrew D Whit. A Perspective on Explanations of Molecular Prediction Models. Journal of chemical theory and computation. 2023-03-27. PMID:36972469. |
chemists can be skeptical in using deep learning (dl) in decision making, due to the lack of interpretability in "black-box" models. |
2023-03-27 |
2023-08-14 |
Not clear |
| Yossra Hussain Ali, Seelammal Chinnaperumal, Raja Marappan, Sekar Kidambi Raju, Ahmed T Sadiq, Alaa K Farhan, Palanivel Srinivasa. Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things. Bioengineering (Basel, Switzerland). vol 10. issue 2. 2023-02-25. PMID:36829633. |
the deep learning (dl) technique is vital in monitoring and controlling the functioning of the healthcare system and ensuring an effective decision-making process. |
2023-02-25 |
2023-08-14 |
Not clear |
| Yossra Hussain Ali, Seelammal Chinnaperumal, Raja Marappan, Sekar Kidambi Raju, Ahmed T Sadiq, Alaa K Farhan, Palanivel Srinivasa. Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things. Bioengineering (Basel, Switzerland). vol 10. issue 2. 2023-02-25. PMID:36829633. |
this model is adequate for real-time health monitoring systems in the prediction of lung cancer and can enable effective decision-making with the use of dl techniques. |
2023-02-25 |
2023-08-14 |
Not clear |
| Attasit Srisubat, Kankamon Kittrongsiri, Sermsiri Sangroongruangsri, Chalida Khemvaranan, Jacqueline Baras Shreibati, Jack Ching, John Hernandez, Richa Tiwari, Fred Hersch, Yun Liu, Prut Hanutsaha, Varis Ruamviboonsuk, Saowalak Turongkaravee, Rajiv Raman, Paisan Ruamviboonsu. Cost-Utility Analysis of Deep Learning and Trained Human Graders for Diabetic Retinopathy Screening in a Nationwide Program. Ophthalmology and therapy. 2023-02-25. PMID:36841895. |
however, there is still limited health economic evaluation, particularly in low- and middle-income countries, on this subject to aid decision-making for dl adoption. |
2023-02-25 |
2023-08-14 |
human |
| Abolfazl Ghorbani, Fatemeh Davoodi, Kamran Zamanifa. Using type-2 fuzzy ontology to improve semantic interoperability for healthcare and diagnosis of depression. Artificial intelligence in medicine. vol 135. 2023-01-11. PMID:36628789. |
this framework not only paved the way to increasing the accuracy of medical diagnosis and decision-making but also provides the possibility of inference and semantic reasoning using the languages of sparql query and dl query. |
2023-01-11 |
2023-08-14 |
Not clear |
| Muazzam Maqsood, Sadaf Yasmin, Saira Gillani, Farhan Aadil, Irfan Mehmood, Seungmin Rho, Sang-Soo Ye. An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning. ISA transactions. 2022-12-09. PMID:36494214. |
we leveraged the vulnerabilities and decision-making abilities of the dl model in gait-based autonomous surveillance systems when attackers have no access to underlying model gradients/structures using a patch-based black-box adversarial attack with reinforcement learning (rl). |
2022-12-09 |
2023-08-14 |
Not clear |
| Bob Daripa, Scott Lucches. Artificial Intelligence-Aided Headache Classification Based on a Set of Questionnaires: A Short Review. Cureus. vol 14. issue 9. 2022-10-27. PMID:36299975. |
wielding modern technology in the form of artificial intelligence (ai) or deep learning (dl) can utilize the best possible latest computer application in intricate decision-making and enigmatic problem-solving. |
2022-10-27 |
2023-08-14 |
Not clear |
| Benedikt Feuerecker, Maurice M Heimer, Thomas Geyer, Matthias P Fabritius, Sijing Gu, Balthasar Schachtner, Leonie Beyer, Jens Ricke, Sergios Gatidis, Michael Ingrisch, Clemens C Cyra. Artificial Intelligence in Oncological Hybrid Imaging. RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin. 2022-09-28. PMID:36170852. |
given the rapid developments in machine learning (ml) and deep learning (dl) methods, the role of ai will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes. |
2022-09-28 |
2023-08-14 |
Not clear |
| Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer K Antan. A Systematic Evaluation of Ensemble Learning Methods for Fine-Grained Semantic Segmentation of Tuberculosis-Consistent Lesions in Chest Radiographs. Bioengineering (Basel, Switzerland). vol 9. issue 9. 2022-09-22. PMID:36134959. |
automated segmentation of tuberculosis (tb)-consistent lesions in chest x-rays (cxrs) using deep learning (dl) methods can help reduce radiologist effort, supplement clinical decision-making, and potentially result in improved patient treatment. |
2022-09-22 |
2023-08-14 |
Not clear |
| Isha R Chavva, Anna L Crawford, Mercy H Mazurek, Matthew M Yuen, Anjali M Prabhat, Sam Payabvash, Gordon Sze, Guido J Falcone, Charles C Matouk, Adam de Havenon, Jennifer A Kim, Richa Sharma, Steven J Schiff, Matthew S Rosen, Jayashree Kalpathy-Cramer, Juan E Iglesias Gonzalez, W Taylor Kimberly, Kevin N Shet. Deep Learning Applications for Acute Stroke Management. Annals of neurology. 2022-06-11. PMID:35689531. |
recent advances in deep machine learning (dl) offer new strategies for harnessing computational medical image analysis to inform decision-making in acute stroke. |
2022-06-11 |
2023-08-14 |
Not clear |
| Thavavel Vaiyapuri, Prasanalakshmi Balaji, Shridevi S, Haya Alaskar, Zohra Sba. Computational Intelligence-Based Melanoma Detection and Classification Using Dermoscopic Images. Computational intelligence and neuroscience. vol 2022. 2022-06-10. PMID:35685142. |
recently, computational intelligence (ci) and deep learning (dl) techniques are utilized for effective decision-making in the biomedical field. |
2022-06-10 |
2023-08-14 |
Not clear |
| Mahmoud Ragab, Ehab Bahaudien Ashary, Wajdi H Aljedaibi, Ibrahim R Alzahrani, Anil Kumar, Deepak Gupta, Romany F Mansou. A novel metaheuristics with adaptive neuro-fuzzy inference system for decision making on autonomous unmanned aerial vehicle systems. ISA transactions. 2022-05-06. PMID:35523604. |
in addition, high resolution remote sensing images need to be classified for effective decision making using deep learning (dl) models. |
2022-05-06 |
2023-08-13 |
Not clear |
| Abdelgader Alamrouni, Fidan Aslanova, Sagiru Mati, Hamza Sabo Maccido, Afaf A Jibril, A G Usman, S I Abb. Multi-Regional Modeling of Cumulative COVID-19 Cases Integrated with Environmental Forest Knowledge Estimation: A Deep Learning Ensemble Approach. International journal of environmental research and public health. vol 19. issue 2. 2022-01-21. PMID:35055559. |
the outcomes of the two scenarios indicate the superiority of arima time series and dl models in further decision making for fk. |
2022-01-21 |
2023-08-13 |
Not clear |