AIMC Topic: Humans

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A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens.

Cancer cytopathology
BACKGROUND: Although deep learning algorithms for clinical cytology have recently been developed, their application to practical assistance systems has not been achieved. In addition, whether deep learning systems (DLSs) can perform diagnoses that ca...

Gender blindness: On health and welfare technology, AI and gender equality in community care.

Nursing inquiry
Digital health and welfare technologies and artificial intelligence are proposed to revolutionise healthcare systems around the world by enabling new models of care. Digital health and welfare technologies enable remote monitoring and treatments, and...

Commentary: the ethical challenges of machine learning in psychiatry: a focus on data, diagnosis, and treatment.

Psychological medicine
The clinical interview is the psychiatrist's data gathering procedure. However, the clinical interview is not a defined entity in the way that 'vitals' are defined as measurements of blood pressure, heart rate, respiration rate, temperature, and oxyg...

Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach.

NeuroImage
Speech comprehension in natural soundscapes rests on the ability of the auditory system to extract speech information from a complex acoustic signal with overlapping contributions from many sound sources. Here we reveal the canonical processing of sp...

A call to action: concerns related to artificial intelligence.

Oral surgery, oral medicine, oral pathology and oral radiology

Soft and self constrained clustering for group-based labeling.

Medical image analysis
When using deep neural networks in medical image classification tasks, it is mandatory to prepare a large-scale labeled image set, and this often requires significant effort by medical experts. One strategy to reduce the labeling cost is group-based ...

Deep learning for predicting COVID-19 malignant progression.

Medical image analysis
As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first as...

[Machine learning and suicide prevention: is an algorithm the solution?].

Nederlands tijdschrift voor geneeskunde
Suicide is inherently difficult to predict. Epidemiological research identified many general risk factors such as a depression, but these predictors have limited predictive power. Machine learning offers a set of tools that can combine hundreds of pr...

Estimating Player Positions from Padel High-Angle Videos: Accuracy Comparison of Recent Computer Vision Methods.

Sensors (Basel, Switzerland)
The estimation of player positions is key for performance analysis in sport. In this paper, we focus on image-based, single-angle, player position estimation in padel. Unlike tennis, the primary camera view in professional padel videos follows a de f...