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Towards Transparency by Design for Artificial Intelligence

Heike Felzmann, Eduard Fosch‐Villaronga, Christoph Lutz, Aurelia Tamò‐Larrieux • Science and Engineering Ethics (2020)

In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making (ADM) environments....

OPENALEX cc-by DOI: https://doi.org/10.1007/s11948-020-00276-4 PMC: 7755865

Artificial intelligence in plant breeding

Muhammad Amjad Farooq, Shang Gao, Muhammad Adeel Hassan, Zhangping Huang et al. • Trends in Genetics (2024)

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing nume...

OPENALEX cc-by-nc DOI: https://doi.org/10.1016/j.tig.2024.07.001

Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

Jennifer Viberg Johansson, Karin Dembrower, Fredrik Strand, Åsa Grauman • BMJ Open (2024)

Background Understanding women’s perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to e...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2024-084014

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Heather Marriott, Renata Kabiljo, Guy P Hunt, Ahmad Al Khleifat et al. • Acta Neuropathologica Communications (2023)

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40478-023-01686-8

Record‐High Latent Heat, Ultra‐Fast Relaxation and Closed‐Loop Recycling Double‐Brush Polymer Networks for Self‐Adaptive Thermal Interface Management

Qiguang Liu, Yanyun Li, Zhenghao Wu, Junjie Cheng et al. • Advanced Science (2026)

ABSTRACT In the era of artificial intelligence (AI)‐driven high‐performance computing, phase change materials (PCMs) are critical for high‐flux thermal management. PCMs are evolving toward high enthalpy, low interfacial thermal resistance (...

DOAJ Open Access (DOAJ) DOI: 10.1002/advs.202521482

An automated deep learning framework for brain tumor classification using MRI imagery

Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro et al. • Scientific Reports (2025)

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-02209-2

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan et al. • Results in Engineering (2024)

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2024.103289

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Ke Guan, Markus Rupp, Thomas Kurner, Cesar Briso et al. • IEEE Access (2020)

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3037635

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography

Changhee Yun, Bomi Eom, Sungjun Park, Chanho Kim et al. • Sensors (2023)

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052864

Can artificial intelligence transform higher education?

Tony Bates, Cristóbal Cobo, Olga Mariño, Steve Wheeler • International Journal of Educational Technology in Higher Education (2020)

Many have argued that the development of artificial intelligence has more potential to change higher education than any other technological advance.For instance, Klutka et al. ( 2018) has listed the following goals for AI in higher educatio...

OPENALEX cc-by DOI: https://doi.org/10.1186/s41239-020-00218-x

Artificial intelligence in glaucoma

Chengjie Zheng, Thomas V. Johnson, Aakriti Garg Shukla, Michael Vincent Boland • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000552

Creativity and Artificial Intelligence

Francisco C. Pereira (2007)

Creativity and Artificial Intelligence: A Conceptual Blending Approach takes readers into a computationally plausible model of creativity. Inspired by a thorough analysis of work on creativity from the areas of philosophy, psychology, cogni...

OPENALEX DOI: https://doi.org/10.1515/9783110198560

Uncertainty in artificial intelligence

Simon Parsons • The Knowledge Engineering Review (1994)

The first conference on Uncertainty in Artificial Intelligence was held in 1985 by a group of people who felt that their views on the use of probability theory were not receiving a fair hearing from the rest of the Al community. At the time...

OPENALEX Open Access DOI: https://doi.org/10.1017/s0269888900006597