Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 16,081 to 16,090 of 213,401 articles

Visual design and digital transformation of imaging under artificial intelligence technology.

Scientific reports May 20, 2026
This study proposes a conditional hierarchical generative adversarial network (GAN) model for intelligent visual design, aiming to explore new modes of human-machine collaboration and promote digital transformation in the design field. The proposed m... read more 

AI-driven volumetric approach for automatic chemotherapy response assessment in colorectal liver metastases.

European radiology May 20, 2026
OBJECTIVES: This study evaluates the clinical utility of an artificial intelligence (AI)-driven volumetric approach for assessing treatment response in colorectal liver metastases (CRLM) compared to conventional RECIST 1.1 measurements. METHODS: We d... read more 

AI-driven qualitative skill assessment in laparoscopic training: a prospective observational study.

NPJ digital medicine May 20, 2026
Qualitative assessment of surgical skills is central to proficiency-based training but remains difficult to scale due to its reliance on expert evaluation. While simulator-derived metrics offer objective data, they largely fail to capture qualitative... read more 

Machine learning based detection of covert communications under jamming interference.

Scientific reports May 20, 2026
In large-scale Internet of Things (IoT) networks, detecting covert communications-hidden transmissions that evade monitoring-is essential to prevent misuse of wireless infrastructure. However, challenges such as fading, noise, jamming interference, a... read more 

Optimizing AI implementation for surgery: recommendations for infrastructure and deployment in the operating room.

NPJ digital medicine May 20, 2026
Recent years have seen a surge in the development of Artificial Intelligence (AI) technologies to enhance intraoperative decision-making and improve patient safety. Yet, real-world evidence on their implementation remains limited. This study evaluate... read more 

Multi-scale buffer analysis and explainable machine learning identify urban form factors and thresholds for waterlogging in Shenzhen urban villages during 9·7 rainstorm.

Scientific reports May 20, 2026
Under the combined pressures of extreme rainfall and rapid urbanization, urban waterlogging has become increasingly severe. As high-density and low-income settlements, urban villages are particularly vulnerable. Taking the "9·7" extreme rainstorm eve... read more 

Phenotypic AI-based design of cell-specific small molecule cytotoxics.

Communications chemistry May 20, 2026
Artificial intelligence is transforming drug discovery by enabling exploration of vast chemical spaces and the design of new molecules with tailored properties. However, most approaches focus on chemical features or protein binding, leaving phenotypi... read more 

Deep learning for predicting patient drug response by transferring gene-level and cell-level knowledge to tumors.

NPJ precision oncology May 20, 2026
Prediction of patient-level drug response is critical for precision oncology but remains limited by the scarcity of clinical data. While machine learning models trained on cell lines offer a scalable alternative, biological differences introduce doma... read more 

IALA-BPNN: superior house price prediction through multi-strategy optimized Artificial Lemming Algorithm and BP neural network.

Scientific reports May 20, 2026
Against this backdrop of a global economic downturn, the real estate market exhibits characteristics of both a consumer good and an investment asset, with housing prices displaying fluctuating nonlinear trends. Predicting these trends holds significa... read more 

Predicting sperm retrieval success in salvage testicular sperm extraction: a machine learning perspective.

International journal of impotence research May 20, 2026
This multicenter retrospective observational study aimed to identify predictive factors for successful secondary testicular sperm extraction (TESE) using advanced machine learning (ML) models. Data from 503 infertile men who underwent secondary TESE ... read more 
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