Digital Imaging and Communications in Medicine (#DICOM) is the standard for the communication and management of #medicalimaging information and related data [1]. An image saved in DICOM format contains an image from a medical scan, such as an ultrasound, CT (computed tomography) scan or MR (magnetic resonance) image. DICOM files may also include identification data for patients in its metadata such as Name, Birthday or type of machine that performed the imaging test. Images s

Artificial intelligence (#AI), through Deep Learning (#DL), allows to analyse a great number of images and extract specific features. Convolutional neural networks are one of the most used systems for this purpose. These networks have a great capacity to recognize medical images. For this reason, AI have created great attention in its recent introduction in the medical field. These technologies are expected to solve many of the current problems in diagnosis and reduce miss r

As we commented in previous posts of this blog, Machine learning (#ML) is a subset of techniques within the concept of #ArtificialIntelligence that allow machine to perform activities to which to which they have not been programmed to. This programming bases on the type of data available and the labels of this data. In this post we will review some important concepts or prediction models inside Machine Learning that are considered the initiators of what now we know as Convolu

Pancreatic cancer (PC) is usually diagnosed at a late stage and the survival rate is often very low. Getting to know risk factors is of key importance for #EarlyDiagnosis. On the one hand, individuals that could benefit of an inclusion in a screening programme must be identified. On the other hand, it is crucial to understand which are the most appropriate tools for PC diagnosis and follow-up. Up to now, there is no diagnostic test considered ideal for #pancreatic cancer scre

As any young startup or any entrepreneur with a revolutionary idea and no prior experience in the field, maybe you went through the internet looking for the best #books and #podcasts to know more about #entrepreneurship. At least we did it. We looked for #SuccessStories, #StartupStrategies or any other concept that could help us to better understand this (for us, new) ecosystem. What we found was a huge and very overwarming quantity of options in multiple languages. So, we wo

It’s fair to say that 2020 has been a year like no other... However, among all the challenges, there have also been many things worth celebrating and there have been plenty of lessons learned along the way. Now is a great time to reflect back on the year we’ve just had. We’ve learned a lot this year… we’ve learned the difference between hygienic and surgical mask, how toilet paper is worth its weight in gold and now we know what a pangolin is. We’ve also discovered a lot of v

Pancreatic cancer is a highly fatal disease with less than a 10% of 5-year #survival rate. The high mortality rate is mainly caused by the lack of highly sensitive and specific tools to detect the disease in an #early stage, and therefore most of the patients are diagnosed in advanced tumor stages. The key to improving survival of pancreatic cancer rests upon early detection of this neoplasm when surgery is possible and hence, it is still a potentially curable stage. Accordin

Pancreatic cystic lesions are increasingly common incidental findings on abdominal imaging tests. However, the prevalence of pancreatic #cysts varies extremely with the method of imaging used and among studies. Still, even by conservative estimations, 3% of all patients undergoing routine computed tomography (#CT) of the abdomen for unrelated indications are now incidentally found to have a pancreatic cyst [1], [2]. And if the prevalence is detected by #MRI, it ranges from 13

You might have heard several times that the key to success is not the idea but the path you follow to make it attractive to the customers, and it is indeed that. In the healthcare industry, if you are developing products to make the diagnosis more accurate, make the doctor’s life easier or make the diagnosis faster you shall not only think about how good your idea is, or if your customer are willing to use it, you shall think how to get it into market, and this forces you to

As you probably know, and probably you already heard several times, the digital transformation of the healthcare sector is here. That means that several technologies have finally taken the lead to a new kind of health services, more accurate, personalized, portable, and private. As for many other things in our lives, we don’t have the time to take care of our health the way we used to, we want everything to happen when, where and how we need, according to our live routines. T

I had the opportunity to sit down and talk with Tamar Garzón, a Medical Internist at Hospital Santa Caterina in Girona. Tamar explains in this interview the strategies of the hospital, and the extraordinary effort her team was going through to manage the crisis. Hospital Santa Caterina is a health organization located in Girona, Spain. Due to its geographical location and the fast spread of the coronavirus, the hospital and its staff had to proactively adapt and to adjust to

COVID-19 pandemic has transformed our world: our routines, relationships, jobs, and every single aspect of our lives. Besides the humanitarian tragedy, we now all know the terrible effects it had on economy and business. Luckily, the situation have brought some positive things too, we saw how innovation and collaboration became the keys to start many social projects and how citizens, associations and private companies took a step forward and developed solutions for many of th

Both, #neuroscience and deep learning face a similar challenge: how do neural networks, consisting of interconnected elements, transform representations of stimuli across multiple processing stages to implement a wide range of complex computations and interactive responses? Artificial neural networks are computing systems slightly inspired by the biological neural networks that constitute a brain. The connections between neurons in the brain are much more complex than those o

Based on the previous post we did in which we made an introduction on #DeepLearning, we continue now presenting the typical network architecture used nowadays to solve the three main tasks of deep learning in image processing: image classification, object detection and image segmentation. 1. Convolutional Neural Networks (CNNs) 1: Example of CNN applied on medical image, [2]. CNNs or ConvNets are feed-forward neural networks that use a spatial-invariance trick to efficiently

Nowadays the healthcare sector is trendy, no doubt. Due to the COVID-19 situation everyone is talking about vaccines, serological tests, antibodies, ARN and even more complex concepts about which half of the people had not even heard about some time ago. Exactly the same happens with businesses, the pandemic speeded up the appearance of many new companies and the terms #MedTech, #Digitalhealth, #eHealth and many others are now in the media almost every day. If you are wanderi

#Diabetes is a major comorbidity of COVID-19, being a key risk factor for developing severe #COVID19 [1]. Indeed, people with the condition are more likely to die [2]. This is an important fact that our AI-based medical assistant, #AIMedAssist, takes into account to predict the evolution of a patient infected by SARS-CoV-2. The relationship goes even further, since diabetes is not only associated with an increased risk of severe COVID-19, but also new-onset diabetes and assoc

The coronavirus (SARS-CoV-2) pandemic continues to spread, confronting healthcare professionals worldwide with unprecedented clinical and operational challenges. At Sycai Technologies, we are aware of the urgency and complexity of the current situation, and we are working hard to provide the best possible support to healthcare personnel at the most critical stages of the #COVID-19 patient care: diagnosis and prognosis. With our AI-based tool, we can accurately identify abnorm

Did you know that the number of pancreatic cystic lesions diagnosed has significantly increased in recent years? It is mainly due to the great improvement in radiological imaging techniques, ageing of the population and increase in awareness of health professionals [1]. Diagnosing these lesions is extremely important as they may have malignant potential and its early recognition could greatly improve outcomes of pancreatic cancer, one of the most lethal diseases. The presence

Pancreatic cancer is a lethal condition with poor outcomes and an increasing incidence, being the 4th leading cause of death by cancer in Europe with less than 5 months of average survival time after diagnosis. The lethal nature of this disease requires an early differential diagnosis of pancreatic cysts, which are identified in up to 16% of normal subjects, and some of which will evolve into pancreatic cancer. However, in autopsy studies, the prevalence of these pancreatic c

Perhaps you have already heard in the news or in your daily work terms like “#deeplearning”, “#machinelearning” or “convolutional neural network”. Over the last ten years, these words have spread mouth to mouth quick due to, mainly, the appearance of Tesla and semi-autonomous driving vehicles. However, the truth is, deep learning was there long before Tesla revolutionized the automotive industry. In the middle of 20th century, Machine learning techniques started being applied