AIMC Topic: Humans

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AI potential in PET/CT cancer imaging.

Hellenic journal of nuclear medicine
Positron emission tomography/computed tomography (PET/CT) is a hybrid medical imaging technique that combines PET and CT to provide detailed images of the body's anatomical structures and metabolic activity. It is frequently used for oncology and oth...

Effect of patient-contextual skin images in human- and artificial intelligence-based diagnosis of melanoma: Results from the 2020 SIIM-ISIC melanoma classification challenge.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: While the high accuracy of reported AI tools for melanoma detection is promising, the lack of holistic consideration of the patient is often criticized. Along with medical history, a dermatologist would also consider intra-patient nevi pa...

iDCNNPred: an interpretable deep learning model for virtual screening and identification of PI3Ka inhibitors against triple-negative breast cancer.

Molecular diversity
Triple-negative breast cancer (TNBC) lacks estrogen, progesterone, and HER2 expression, accounting for 15-20% of breast cancer cases. It is challenging due to low therapeutic response, heterogeneity, and aggressiveness. The PI3Ka isoform is a promisi...

Sustainable Silk Fibroin Ionic Touch Screens for Flexible Biodegradable Electronics with Integrated AI and IoT Functionality.

Advanced materials (Deerfield Beach, Fla.)
The increasing prevalence of electronic devices has led to a significant rise in electronic waste (e-waste), necessitating the development of sustainable materials for flexible electronics. In this study, silk fibroin ionic touch screen (SFITS) is in...

Frequency-adjusted borders ordinal forest: A novel tree ensemble method for ordinal prediction.

The British journal of mathematical and statistical psychology
Ordinal responses commonly occur in psychology, e.g., through school grades or rating scales. Where traditionally parametric statistical models like the proportional odds model have been used, machine learning (ML) methods such as random forest (RF) ...

Integration of AI-Assisted in Digital Cervical Cytology Training: A Comparative Study.

Cytopathology : official journal of the British Society for Clinical Cytology
OBJECTIVE: This study aimed to investigate the supporting role of artificial intelligence (AI) in digital cervical cytology training.

Effective analysis of thyroid toxicity and mechanisms of acetyltributyl citrate using network toxicology, molecular docking, and machine learning strategies.

Toxicology
The growing prevalence of environmental pollutants has raised concerns about their potential role in thyroid dysfunction and related disorders. Previous research suggests that various chemicals, including plasticizers like acetyl tributyl citrate (AT...

ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks.

Computers in biology and medicine
Adenosine triphosphate plays a vital role in providing energy and enabling key cellular processes through interactions with binding proteins. The increasing amount of protein sequence data necessitates computational methods for identifying binding si...

CE-Net: Cascade attention and context-aware cross-level fusion network via edge learning guidance for polyp segmentation.

Computers in biology and medicine
Colorectal polyps are one of the most direct causes of colorectal cancer. Polypectomy can effectively block the process of colorectal cancer, but accurate polyp segmentation methods are required as an auxiliary means. However, there are several chall...