Background: Thanks to the rapid development of computer-based systems and deep-learning-based algorithms, artificial intelligence (AI) has long been integrated into the healthcare field. AI is also particularly helpful in image recognition, surgical assistance and basic research. Due to the unique nature of dermatology, AI-aided dermatological diagnosis based on image recognition has become a modern focus and future trend. Key scientific concepts of review: The use of 3D imaging systems allows clinicians to screen and label skin pigmented lesions and distributed disorders, which can provide an objective assessment and image documentation of lesion sites. Dermatoscopes combined with intelligent software help the dermatologist to easily corre...
A substantial body of research has been published on artificial intelligence applications in skin ca...
Skin cancer, previously known to be a common disease in Western countries, is becoming more common i...
Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Li...
In medicine, dermatology is a promising pioneer for the use of artificial intelligence (AI). In derm...
Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is ra...
In recent years, an increasing enthusiasm has been observed towards artificial intelligence and mac...
This thesis investigates the use of Artificial Intelligence (AI) for skin cancer diagnosis. It explo...
In the past, the skills required to make an accurate dermatological diagnosis have required exposure...
Artificial intelligence (AI) is being used in almost all aspects of life. The AI can assist medical ...
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available ...
Skin cancer is a serious public health problem with a sharply increasing incidence in recent years, ...
Background: Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagn...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Background: Artificial intelligence is advancing at an accelerated pace into clinical applications, ...
Machine learning (ML) has the potential to improve the dermatologist's practice from diagnosis to pe...
A substantial body of research has been published on artificial intelligence applications in skin ca...
Skin cancer, previously known to be a common disease in Western countries, is becoming more common i...
Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Li...
In medicine, dermatology is a promising pioneer for the use of artificial intelligence (AI). In derm...
Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is ra...
In recent years, an increasing enthusiasm has been observed towards artificial intelligence and mac...
This thesis investigates the use of Artificial Intelligence (AI) for skin cancer diagnosis. It explo...
In the past, the skills required to make an accurate dermatological diagnosis have required exposure...
Artificial intelligence (AI) is being used in almost all aspects of life. The AI can assist medical ...
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available ...
Skin cancer is a serious public health problem with a sharply increasing incidence in recent years, ...
Background: Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagn...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Background: Artificial intelligence is advancing at an accelerated pace into clinical applications, ...
Machine learning (ML) has the potential to improve the dermatologist's practice from diagnosis to pe...
A substantial body of research has been published on artificial intelligence applications in skin ca...
Skin cancer, previously known to be a common disease in Western countries, is becoming more common i...
Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Li...