Researchers have used 3D bioprinting technology to create custom-shaped cartilage. They aim to make it easier for surgeons to safely restore the features of skin cancer patients living with nasal cartilage defects after surgery.
Researchers have developed an approach to print tiny tissues that look and function almost like their full-sized counterpart.
A team from the Universitat Politècnica de València (UPV) has developed a new mobile application that facilitates the continuous monitoring of the quality of life of cancer patients.
The neural network detects anomalies in medical images more successfully than general-purpose solutions.
AI-based solution FAITH is designed to monitor the mental health status of people who have undergone cancer treatment.
An electrical impedance tomography toolkit lets users design and fabricate health and motion sensing devices.
Studying these organoids could help researchers develop and test new treatments for pancreatic cancer.
Realistic mini-lungs, grown in lab dishes, feature all cell types that make up the human organ, allowing for “Phase 0” testing of new treatments for respiratory diseases.
An artificial intelligence blood testing technology was found to detect over 90% of lung cancers in samples from nearly 800 individuals with and without cancer.
Scientists at have shown that diagnostic nanoparticles could be used to monitor tumor recurrence after treatment or to perform routine cancer screenings.
A tool, based on machine learning methods, that evaluates the potential contribution of all possible mutations in a gene in a given type of tumour to the development and progression of cancer.
The Scar Free Foundation has launched a research programme that aims to revolutionise surgeons’ ability to reconstruct nose and ear cartilage in patients affected by facial difference.
Researchers used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu.
Researchers have developed a holographic technique that can rapidly reconstruct microscopic images of samples with up to 50-fold acceleration compared to existing methods.
A team of engineers from Rensselaer Polytechnic Institute and clinicians from Massachusetts General Hospital developed a deep learning algorithm that can help assess a patient's risk of cardiovascular disease with the same low-dose computerized tomography (CT) scan used to screen for lung cancer.
An artificial intelligence (AI) program accurately predicts the risk that lung nodules detected on screening CT will become cancerous, according to a new study.
Neural network framework may increase radiologist's confidence in assessing the type of lung cancer on CT scans, informing individualized treatment planning.
A study from Stanford University found limitations in the Food and Drug Administration’s approval process.
Engineers have created a tiny wireless implant that can provide real-time measurements of tissue oxygen levels deep underneath the skin.
Researchers have tested a sensor for measuring hydrogen peroxide concentrations near cell membranes. The sensor has the potential to become a tool for new cancer therapies.
A deep learning model that can predict how human genes and medicines will interact has identified at least 10 compounds that may hold promise as treatments for COVID-19.
Scientists have presented a new method for configuring self-learning algorithms for a large number of different imaging datasets – without the need for specialist knowledge or very significant computing power.
Researchers are developing solutions designed to enable the analysis of breath gas to assist with the diagnosis of disease.
Researchers have developed AI technology that offers a glimpse of the future of precision medicine, and unprecedented predictive power to clinicians caring for individuals with the life-limiting condition.
Scientists have made a breakthrough in their work to develop semi-autonomous colonoscopy, using a robot to guide a medical device into the body.
Find out more about how scientists and physician are using AI to make contributions in the fight against the coronavirus.
Using specialized nanoparticles, engineers have developed a way to monitor pneumonia or other lung diseases by analyzing the breath exhaled by the patient.
Researchers have created an artificial neural network that analyzes lung CT scans to provide information about lung cancer severity that can guide treatment options.
Researchers have developed a microneedle patch to deliver mesenchymal stem cells (MSCs) into the skin.
Computer scientists working with pathologists have trained an AI tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment.
An anaesthesia team used 3D printing and virtual reality to produce an exact model of the airway of a 7-year-old girl in order to prepare properly for an operation to remove part of her lung.
The future of socially distanced lung and heart health monitoring could lie in an inconspicuous yet incredibly sensitive chip.
behold.ai has been issued with a CE Mark Class lla certification in the UK and EU for its AI-based technology that can diagnose chest X-rays as ‘normal’.
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
“AI is the biggest technological breakthrough of our lifetime. It will boost the entire healthcare ecosystem and will eventually re-invent the way we deliver medicine entirely.”
To better leverage cancer data for research, scientists are developing an artificial intelligence-based natural language processing tool to improve information extraction from textual pathology reports.
Researchers have developed a tumor biosensing chip that can help determine the optimum dosage of chemotherapy required for a cancer patient.
A software tool uses artificial intelligence to recognize cancer cells from digital pathology images — giving clinicians a powerful way of predicting patient outcomes.
Scientists can determine which lung-cancer patients will benefit from expensive immunotherapy.
Radiologists assisted by deep learning based software were better able to detect malignant lung cancers on chest X-rays.
Researchers found that using 3D models to prepare for kidney tumor surgeries resulted in substantial improvements, including shorter operating times.
Researchers used artificial intelligence to develop a new classification method which identifies the primary origins of cancerous tissue based on chemical DNA changes.
Collaborators are developing an endoscopic robotic system with two-handed dexterity at a much smaller scale than existing options.
An AI approach can identify with high accuracy whether a 5-day-old, in vitro fertilized human embryo has a high potential to progress to a successful pregnancy.
Patients could soon get faster and more accurate diagnoses with new software that can automatically detect signs of diabetes, heart disease and cancer from medical images.
Researchers have utilized machine learning capabilities to assist with the challenging task of grading tumor patterns and subtypes of lung adenocarcinoma.
A team of experts led by two University of Michigan researchers calls for attention to this shadow record.
The first comprehensive study comparing the outcomes of robotic surgery to those of traditional open surgery in any organ has found that the surgeries are equally effective in treating bladder cancer.
