AIMC Topic: Humans

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Artificial Intelligence and the Common Sense of Animals.

Trends in cognitive sciences
The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the und...

Understanding Human Intelligence through Human Limitations.

Trends in cognitive sciences
Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may diffe...

MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer.

EBioMedicine
BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 expression level and predict pathologic response (pCR) in HER2 overexpressing breast cancer patients receiving neoadjuvant chemotherapy (NAC).

Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.

EBioMedicine
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...

Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging.

Aging cell
We previously identified 529 proteins that had been reported by multiple different studies to change their expression level with age in human plasma. In the present study, we measured the q-value and age coefficient of these proteins in a plasma prot...

[Autonomous assitive robots for older people at home: An exploratory study : "He is always there for me-and I for him too"].

Zeitschrift fur Gerontologie und Geriatrie
The use of autonomous assistive robots in the domestic environment of old people and the possible effects on the quality of life is a relatively new field of research. Given the relatively limited technical robustness of these robots, autonomous assi...

Automatic segmentation, classification, and follow-up of optic pathway gliomas using deep learning and fuzzy c-means clustering based on MRI.

Medical physics
PURPOSE: Optic pathway gliomas (OPG) are low-grade pilocytic astrocytomas accounting for 3-5% of pediatric intracranial tumors. Accurate and quantitative follow-up of OPG using magnetic resonance imaging (MRI) is crucial for therapeutic decision maki...

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Scientific reports
Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In clinical practice, facial erythema of patients with diabetes is evaluated based on subjective observati...

Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Scientific reports
Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we perf...

Clinical predictive modelling of post-surgical recovery in individuals with cervical radiculopathy: a machine learning approach.

Scientific reports
Prognostic models play an important role in the clinical management of cervical radiculopathy (CR). No study has compared the performance of modern machine learning techniques, against more traditional stepwise regression techniques, when developing ...