[HTML][HTML] Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities
The past decade has seen significant progress in artificial intelligence (AI), which has
resulted in algorithms being adopted for resolving a variety of problems. However, this …
resulted in algorithms being adopted for resolving a variety of problems. However, this …
Deep learning applications in breast cancer histopathological imaging: diagnosis, treatment, and prognosis
B Jiang, L Bao, S He, X Chen, Z Jin, Y Ye - Breast Cancer Research, 2024 - Springer
Breast cancer is the most common malignant tumor among women worldwide and remains
one of the leading causes of death among women. Its incidence and mortality rates are …
one of the leading causes of death among women. Its incidence and mortality rates are …
Rapsai: Accelerating machine learning prototyping of multimedia applications through visual programming
In recent years, there has been a proliferation of multimedia applications that leverage
machine learning (ML) for interactive experiences. Prototyping ML-based applications is …
machine learning (ML) for interactive experiences. Prototyping ML-based applications is …
Who do we mean when we talk about visualization novices?
As more people rely on visualization to inform their personal and collective decisions,
researchers have focused on a broader range of audiences, including “novices.” But …
researchers have focused on a broader range of audiences, including “novices.” But …
[HTML][HTML] Pitfalls in developing machine learning models for predicting cardiovascular diseases: challenge and solutions
YQ Cai, DX Gong, LY Tang, Y Cai, HJ Li… - Journal of Medical …, 2024 - jmir.org
In recent years, there has been explosive development in artificial intelligence (AI), which
has been widely applied in the health care field. As a typical AI technology, machine …
has been widely applied in the health care field. As a typical AI technology, machine …
Visual analytics for machine learning: A data perspective survey
The past decade has witnessed a plethora of works that leverage the power of visualization
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …
Talaria: Interactively optimizing machine learning models for efficient inference
On-device machine learning (ML) moves computation from the cloud to personal devices,
protecting user privacy and enabling intelligent user experiences. However, fitting models …
protecting user privacy and enabling intelligent user experiences. However, fitting models …
Searching discriminative regions for convolutional neural networks in fundus image classification with genetic algorithms
Y Rong, T Lin, H Chen, Z Fan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep convolutional neural networks (CNNs) have been widely used for fundus image
classification and have achieved very impressive performance. However, the explainability …
classification and have achieved very impressive performance. However, the explainability …
[HTML][HTML] Using crayfish behavior assay as a simple and sensitive model to evaluate potential adverse effects of water pollution: Emphasis on antidepressants
ME Suryanto, CT Luong, RD Vasquez… - Ecotoxicology and …, 2023 - Elsevier
The freshwater crayfish, Procambarus clarkii is an excellent aquatic animal model that is
highly adaptable and tolerant. P. clarkii is widely used as a toxicity model to study various …
highly adaptable and tolerant. P. clarkii is widely used as a toxicity model to study various …
Causal signal temporal logic for the environmental control and life support system's fault analysis and explanation
Modern cyber-physical systems would often fall victim to unanticipated anomalies. Humans
are still required in many operations to troubleshoot and respond to such anomalies, such …
are still required in many operations to troubleshoot and respond to such anomalies, such …