Results 231 to 240 of about 7,172,817 (283)

Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide an overview of potential biases resulting from the utilization of artificial intelligence (AI) in otolaryngology and techniques to mitigate them. Data Sources Literature review and expert opinion. Conclusions AI promises to fundamentally transform medicine.
Matthew T. Ryan, David A. Gudis
wiley   +1 more source

Automating the creation of fashion patterns using deep learning algorithms. [PDF]

Front Artif Intell
Alsabhi R.
europepmc   +1 more source

Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley   +1 more source

A comparative evaluation of quantum machine learning architectures for breast cancer classification using clinical and genomic data. [PDF]

Front Artif Intell
Allena S, G S S, Chandrasekaran B.
europepmc   +1 more source

CTGAN-Based Data Augmentation and XGBoost-LSTM Strength Prediction of CSG. [PDF]

Materials (Basel)
Li G, Zhang Y, Tian Q, Guo L, Chai Q.
europepmc   +1 more source

CASCADENCE: a layered cascade defense mechanism for federated learning. [PDF]

Sci Rep
Hashmi SW, Shukla RM, Bhunia S.
europepmc   +1 more source

Review on enhancing clinical decision support system using machine learning

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood, Usman Naseem, Junaid Rashid, Jungeun Kim, Imran Razzak   +4 more
wiley   +1 more source

AI-driven adaptive adversaries and the erosion of cryptographic trust in public key systems. [PDF]

J Anal Sci Technol
Radanliev P.
europepmc   +1 more source

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source