AIMC Topic: Humans

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Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.

BMC medical research methodology
In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs o...

Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images.

Breast cancer research : BCR
BACKGROUND: Nottingham histological grade (NHG) is a well established prognostic factor in breast cancer histopathology but has a high inter-assessor variability with many tumours being classified as intermediate grade, NHG2. Here, we evaluate if Dee...

Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre.

BMC health services research
BACKGROUND: Artificial intelligence (AI) technologies are expected to "revolutionise" healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explor...

Classification of short and long term mild traumatic brain injury using computerized eye tracking.

Scientific reports
Accurate, and objective diagnosis of brain injury remains challenging. This study evaluated useability and reliability of computerized eye-tracker assessments (CEAs) designed to assess oculomotor function, visual attention/processing, and selective a...

MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images.

Scientific reports
Medical image segmentation has made a significant contribution towards delivering affordable healthcare by facilitating the automatic identification of anatomical structures and other regions of interest. Although convolution neural networks have bec...

Automatized self-supervised learning for skin lesion screening.

Scientific reports
Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body sc...

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study.

Journal of medical Internet research
BACKGROUND: Current embryo assessment methods for in vitro fertilization depend on subjective morphological assessments. Recently, artificial intelligence (AI) has emerged as a promising tool for embryo assessment; however, its clinical efficacy and ...

Reply: Artificial Intelligence Algorithms Are Not Clairvoyant.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine

Artificial Intelligence Algorithms Are Not Clairvoyant.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine

A Deep-Learning-Based Partial-Volume Correction Method for Quantitative Lu SPECT/CT Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
With the development of new radiopharmaceutical therapies, quantitative SPECT/CT has progressively emerged as a crucial tool for dosimetry. One major obstacle of SPECT is its poor resolution, which results in blurring of the activity distribution. Es...