18 papers · ranked by Valyu relevance
Alisa J. Hamilton, Alexandra T. Strauss, Diego A. Martinez, Jeremiah S. Hinson + 3 more
'Jeremiah S. Hinson' 'Scott Levin' 'Gary Lin' 'Eili Y. Klein'] Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a subtype of AI; it refers to the ability of computers to draw conclusions (ie, learn) from data without…
Laura Elena Mendoza Bolivar, Michael Satzer, Jennifer M. Lynch
Artificial intelligence (AI) has exploded in public awareness over recent years and is already beginning to reshape the health care sector. Yet, even as AI becomes more prevalent, it remains a mystery to many providers who lack hands-on exposure during their training or on the job. Intended for medical professionals…
Long Chen, Guanqing Liu, Tao Zhang
Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements. Simultaneously, the exponential growth of computational power and big data now promote the application of machine learning for biological research. In this regard, machine learning shows great…
Yiru Jiang, Jing Luo, Danqing Huang, Ya Liu + 1 more
Microorganisms play an important role in natural material and elemental cycles. Many common and general biology research techniques rely on microorganisms. Machine learning has been gradually integrated with multiple fields of study. Machine learning, including deep learning, aims to use mathematical insights to…
Sandra Eloranta, Magnus Boman
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use. In an introduction to predictive modelling using machine learning, we conducted…
Narjice Chafai, Ichrak Hayah, Isidore Houaga, Bouabid Badaoui
The advent of modern genotyping technologies has revolutionized genomic selection in animal breeding. Large marker datasets have shown several drawbacks for traditional genomic prediction methods in terms of flexibility, accuracy, and computational power. Recently, the application of machine learning models in animal…
Absalom E. Ezugwu, Olaide N. Oyelade, Abiodun M. Ikotun, Jeffery O. Agushaka + 1 more
The machine learning (ML) paradigm has gained much popularity today. Its algorithmic models are employed in every field, such as natural language processing, pattern recognition, object detection, image recognition, earth observation and many other research areas. In fact, machine learning technologies and their…
Yasunari Matsuzaka, Yoshihiro Uesawa, Huiyong Sun, Peichen Pan + 1 more
'Jingyu Zhu'] A deep learning-based quantitative structure-activity relationship analysis, namely the molecular image-based DeepSNAP-deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a three-dimensional (3D) structure of a chemical compound. It…
Stephen B Lee, Alexis B Carter, Muhammad Hamis Haider, Seok-Bum Ko + 2 more
Artificial intelligence (AI) is already fundamentally changing society, with medicine being no exception. AI will impact how we practice, how hospitals operate, and even the practice of medicine itself. The use of AI-based products has already begun, with examples including AI scribes and large language models such as…
Pierre Bongrand, Binh P. Nguyen, Fei Guo
During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted to ask whether AI thinking should be durably involved in biomedical research. This problem was addressed by examining three complementary questions (i) What are…
Karl-Patrik Kresoja, Matthias Unterhuber, Rolf Wachter, Holger Thiele + 1 more
A modern-day physician is faced with a vast abundance of clinical and scientific data, by far surpassing the capabilities of the human mind. Until the last decade, advances in data availability have not been accompanied by analytical approaches. The advent of machine learning (ML) algorithms might improve the…
Cheng Xu, Ling-Yun Zhao, Cun-Si Ye, Ke-Chen Xu + 1 more
With the development of artificial intelligence(AI) in computer science and statistics, it has been further applied to the medical field. These applications include the management of infectious diseases, in which machine learning has created inroads in clinical microbiology, radiology, genomics, and the analysis of…
Alessia Nicosia, Nunzio Cancilla, José David Martín Guerrero, Ilenia Tinnirello + 2 more
Artificial Intelligence (AI) is transforming the healthcare field, offering innovative tools for improving the prediction, detection, and management of diseases. In nephrology, AI holds the potential to improve the diagnosis and treatment of kidney diseases, as well as the optimization of renal replacement therapies.…
Paola Patricia Ariza-Colpas, Enrico Vicario, Ana Isabel Oviedo-Carrascal, Shariq Butt Aziz + 7 more
The Assisted Living Environments Research Area-AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative…
David Kasperek, Michal Podpora, Aleksandra Kawala-Sterniuk, Cristinel Ababei + 2 more
'Cristinel Ababei' 'Henry Medeiros' 'Richard J. Povinelli'] In this paper, the authors have compared all of the currently available Apple MacBook Pro laptops, in terms of their usability for basic machine learning research applications (text-based, vision-based, tabular). The paper presents four tests/benchmarks…
Sarinder Kaur Dhillon, Mogana Darshini Ganggayah, Siamala Sinnadurai, Pietro Lio + 2 more
'Pietro Lio' 'Nur Aishah Taib' 'Md Mohaimenul Islam'] The practice of medical decision making is changing rapidly with the development of innovative computing technologies. The growing interest of data analysis with improvements in big data computer processing methods raises the question of whether machine learning can…
Gerardo Ibarra-Vazquez, María Soledad Ramírez-Montoya, Hugo Terashima
'Hugo Terashima'] This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity…
Jörn Lötsch, Alfred Ultsch, Benjamin Mayer, Dario Kringel
Machine learning applications are rapidly increasing in pain research and are applied to patient data, while they seem to be little used in preclinical research.