The art of diagnosing rare skin tumors: Can DL-CNNs enhance dermatologists' diagnostic accuracy?

Importance: Deep learning convolutional neural networks (DL-CNN) achieved diagnostic accuracies comparable to dermatologists in controlled test environments. However, their performance in diagnosing rare skin tumors (RST) remains unclear. This study aimed to evaluate a binary DL-CNN's diagnostic performance in RST and assess the level of support for an international group of dermatologists.

Identifying melanoma among benign simulators - Is there a role for deep learning convolutional neural networks? (MelSim Study).

Importance: Early detection of cutaneous melanoma (CM) is crucial for patient survival, yet avoiding overdiagnosis remains essential. Differentiating CM from benign melanoma simulators (MelSim) is challenging due to overlapping features. Deep learning convolutional neural networks (DL-CNNs) have demonstrated dermatologist-level accuracy in identifying CM.

The power of combined modalities in interactive robot learning.

With the continuous advancement of Artificial intelligence (AI), robots as embodied intelligent systems are increasingly becoming more present in daily life like households or in elderly care. As a result, lay users are required to interact with these systems more frequently and teach them to meet individual needs. Human-in-the-loop reinforcement learning (HIL-RL) offers an effective way to realize this teaching.

Polyclonal antibodies towards abrin and ricin-design and potential application for mass spectrometry-based analysis of human biosamples.

The analysis of highly toxic proteins such as abrin and ricin is challenging but comprehensive analytical methods are essential for their unambiguous identification after ingestion. This study pursued three primary aims at detecting abrin and ricin in human biosamples while ensuring that laboratory staff remain protected from direct exposure to these toxic proteins. First, two polyclonal antibodies (pAB) against specific peptides of abrin-A and ricin should be produced.