A machine learning system has been developed to identify cancer cells based on their light scattering patterns, achieving high accuracy even with cells having similar morphology. The system, which uses dark-field microscopy and machine learning algorithms, has shown promise in distinguishing between different types of cancer cells.
Researchers developed V-UNet, a novel model combining global and local information to address noise and redundant information in medical images. The model achieved competitive segmentation performance while maintaining low computational requirements, promising a more efficient and robust AI-assisted medical image analysis.
Prostate cancer affects 1 in 8 men, with 60% diagnosed in men 65 and older. Clinical trials like Alliance's help improve early detection and treatment, reducing mortality rates by half since 1993. These trials also explore new treatments and survivorship strategies.
Researchers developed a computational model to study aging in 40 types of human tissue, identifying three major aging patterns and underlying molecular changes. Tissues show bimodal structural aging, with accelerated aging from 35-40 and 55-60, coinciding with fertility decline and menopause.
Researchers have found a reliable alternative to bone marrow sampling for children with rhabdomyosarcoma, using PET scans to detect bone marrow involvement with high accuracy. This approach could spare patients from painful procedures and improve diagnostic practices.
USC researchers have developed custom, 3D-printed MRI sensors that provide clearer images of small organs in infants and children. The sensors, which can be customized to individual patients, are made in under 10 minutes and cost around $30.
The Alliance for Clinical Trials in Oncology emphasizes the significance of clinical trials in advancing breast cancer treatments and early detection. The organization's work has led to a 44% decline in breast cancer mortality rates among women since 1989.
A new study reveals that fluctuations in estrogen influence brain connections in rats, using a specialized imaging technique called magnetic resonance elastography (MRE). Researchers hope to translate the findings to humans, exploring how hormonal changes affect brain health in women, particularly during menopause.
Researchers explore how engineered lanthanide carriers can tune the optical and magnetic properties of ions for improved signal contrast and reduced background signals in biomedical imaging. The study highlights opportunities for multimodal imaging, theranostics, and AI-guided probe design.
Recent progress in lanthanide carriers is mapped to improve biomedical imaging and diagnosis, combining optical, X-ray, and magnetic resonance imaging techniques. These carriers enable high-resolution imaging with tunability for different applications, reducing tissue damage and enhancing image clarity.
A Tulane University team is using AI to discover new superconductors, which could improve the nation's electrical grid, medical imaging, and quantum computing. The project combines high-fidelity calculations, physics-aware AI, and experimental measurements to accelerate discovery.
The study creates a radiohybrid approach that labels a single molecule with two different diagnostic radionuclides, enabling long-term visualization of therapeutic agent distribution. This allows for personalized cancer medicine by calculating optimal radiation doses for individual patients.
The AKI-PURIFY survey reveals substantial variability in AKI prevention strategies and KDIGO implementation across ICUs. Despite strong evidence supporting structured preventive approaches, only one-third of respondents reported routine implementation of kidney-protective bundles.
The NHS Clinical Entrepreneur Programme has supported the creation of 691 businesses, generating 5,184 jobs and raising over £1.27 billion in investment. The programme continues to play a critical role in retaining talent within the NHS by enabling clinicians to develop their ventures alongside their clinical careers.
A phase III trial is investigating whether an immune-boosting drug can help keep early-stage lung cancer from coming back after surgery. Researchers aim to enroll 336 participants with stage I non-small cell lung cancer and determine if the treatment reduces recurrence.
A new study suggests that functional brain imaging can help guide accelerated transcranial magnetic stimulation (TMS) for depression, leading to improved symptoms and response rates. The approach uses resting-state functional connectivity analysis to identify individualized treatment targets.
Researchers developed a quick and non-invasive imaging method combined with machine learning to detect precancerous lesions and early-stage cancers in the uterus. The method uses 3D OCT images to provide clear differences among normal tissue, benign endometrium, high-risk precancerous lesions, and endometrial cancer at different stages.
FireANTs, an open-source algorithm, combines AI optimization and geometry to quickly match complex medical images. The new method can accomplish what took weeks in minutes, detecting subtle changes that signal disease or cognitive decline, making it practical for clinical practice.
A new set of consensus standards for classification, annotation, and quality control is being implemented for artificial intelligence applications in dry eye imaging. These standards aim to enhance consistency and multicenter collaboration in AI-assisted diagnosis.
A new study by the University of Southampton has found that reusable catheters are just as safe for patients as single-use ones and do not increase the risk of urinary tract infections. The study followed hundreds of patients for a year and discovered that those who tested reusable catheters used 35 per cent fewer antibiotics.
A new approach enables computers and machines to capture images at higher resolution and faster speed, making it impervious to reflective surfaces. The technology uses a virtual screen created by repurposing the surroundings of specular objects.
A new AI system enables real-time spine positioning and analysis during MRI scans, improving accuracy and reducing variability. The system was tested in a multicenter study involving 1,522 patients, showing significant improvements over manual interpretation for diagnosing lumbar disc herniation and spinal canal stenosis.
A novel antibody, NG101, accelerates the regeneration of damaged spinal cord tissue by neutralizing a protein that blocks nerve fiber growth. This therapy enables new nerve fibers to form functional connections, allowing patients to become more independent and potentially recover arm and hand function.
Researchers developed a novel diagnostic support framework using visual question answering to generate interpretable findings from chest CT images. The system demonstrated strong agreement with reference descriptions and provided clinically meaningful outputs.
SourceMeijo University·JournalInternational Journal of Computer Assisted Radiology and Surgery·TypeComputational simulation/modeling·DateMay 11, 2026
Researchers at Aalto University developed a new ultrasonic needle that can collect 2-3 times more tissue than current biopsy methods, improving cancer diagnosis accuracy. The minimally invasive approach shows strong potential for broader diagnostic use, particularly in rare salivary gland tumors.
After a mild head injury, CSF motion increased in some regions and decreased in others. The technique may help clarify the link between post-traumatic brain conditions and changes in cognitive function.
Researchers developed multiplexed MRI technology, enabling simultaneous imaging of signals from multiple molecules in the brain. The technology provides a comprehensive view of the brain's structure, physiology, and molecular processes, allowing for more precise diagnosis and individualized treatment planning.
The review highlights how retrieval-augmented generation can improve the accuracy, transparency, and clinical reliability of AI tools in cancer care. RAG-enhanced systems produced more accurate results than standard AI models across multiple studies.
SourceSAGE·JournalAI in Precision Oncology·TypeLiterature review·DateApr 30, 2026
The center offers state-of-the-art facilities for practical skills acquisition, digital technologies integration, and innovation in medical procedures. Future physicians will benefit from cadaver training, real-time imaging, and collaborative research opportunities.
The Salk Institute will lead an ARPA-H-funded project to develop ultrasound-sensitive protein tools, wearable ultrasound delivery technology, and a translational path to the clinic for major unmet medical needs. The team aims to create a noninvasive therapy for conditions such as peripheral neuropathy.
City St George's, University of London, is partnering with Paradigm Biopharmaceuticals to test a potential treatment for osteoarthritis. The partnership aims to investigate the mechanism of action of pentosan polysulfate sodium (iPPS) on bone marrow lesions, which are linked to pain in osteoarthritis.
Researchers developed a new multiview DNN structure to capture complex 3D anatomy and physiology from multiple imaging views, improving diagnostic accuracy for cardiovascular conditions. The approach demonstrated better performance than single-view DNNs and provided a viable alternative for other medical imaging modalities.
A specialized AI model, AMIR-GPT, has been developed to improve radiology guideline alignment, outperforming general purpose models in 33.3% of test responses. However, the model's performance varied across performance bands, and qualitative review revealed limitations, such as omissions and deviations from standard recommendations.
Recent advances in photonic nanomaterials and healthcare devices have led to the development of wearable and implantable medical devices. These devices utilize light for precise manipulation of cells and tissues, offering new possibilities for early disease detection, light-based therapies, and personalized precision medicine.
Severe COVID-19 and influenza infections can prime the lungs for cancer development, according to new research. Vaccination, however, largely prevents these changes, suggesting a reduced risk of lung cancer.
Researchers at the University of Queensland have made a breakthrough in understanding the cellular changes that occur in depression. They found that cells in people with depression produce more energy molecules when resting, but have a reduced ability to increase energy production under stress. This study offers a new potential approac...
Generative AI in medical imaging enables data synthesis, image enhancement, and modality translation to improve diagnosis and treatment outcomes. The review discusses challenges and future prospects, including convergence with large-scale foundation models and multimodal information for holistic understanding.
Artificial intelligence can complement human expertise to improve radiology workflows and patient care. The JACR Focus Issue on AI in Workflow Optimization explores the integration of AI technology to enhance efficiency and deliver better care.
A new AI-powered tool, Merlin, has been developed to assess 3D abdominal CT scans, identifying anatomical features and predicting disease onset years in advance. The tool surpassed traditional automated tools in tasks such as diagnosing diseases and predicting patient outcomes, with accuracy rates of up to 81%.
Researchers found that implanted cuff electrodes can trigger unintended nerve stimulation during MRI, causing discomfort or pain. The study recommends more refined guidelines and careful safety considerations to mitigate this risk.
Researchers have developed a non-invasive method to estimate blood oxygen levels in heart failure patients using standard cardiac MRI. This breakthrough could spare thousands from undergoing risky tube procedures, allowing for safer and more frequent monitoring.
A new study discovered two previously unidentified fat distribution types associated with extensive gray matter atrophy and accelerated brain aging in men and women. Individuals with 'pancreatic-predominant' and 'skinny fat' profiles showed increased risk of neurological diseases, cognitive decline, and brain health issues.
A new study from Nationwide Children's Hospital finds that similar to older children and adults, about one fourth of children under six years old who experience a concussion will develop prolonged symptoms. Younger children are more likely to sustain brain injuries due to their size differences and weaker muscles.
A new study suggests that gaps in the nation's stroke transfer system reduce survivors' chances of receiving critical treatment and increase disability. Patients with longer delays in hospital transfer experienced worse disability after their stroke, highlighting missed opportunities for many stroke patients.
A statewide partnership in Michigan led to a significant increase in patients receiving follow-up imaging after aortic aneurysm repair. This resulted in a reduced likelihood of dying within one year of surgery and improved detection of early problems that can lead to device failure or future complications.
Steatotic liver disease can be precisely assessed using three-dimensional ultrafast vascular ultrasound. The technology visualizes subtle microvascular changes, enabling real-time monitoring of disease progression and therapeutic response.
ACCESS-AD aims to address Alzheimer's disease challenges with a coordinated framework for diagnosis, treatment and monitoring. The project combines advanced neuroimaging with digital biomarkers to support early patient identification and personalized treatment pathways.
A new clinical trial, PAGODA, seeks to minimize treatment interruptions and help patients complete their chemotherapy as planned. The trial will test a structured plan to guide doctors in making small, proactive changes to chemotherapy doses to prevent treatment delays.
Researchers developed CardioKG, an AI-driven tool that integrates imaging data with biological databases to predict gene-disease associations and identify new drug opportunities for heart conditions. The study identified potential treatments for atrial fibrillation and heart failure using existing drugs like methotrexate and gliptins.
The new framework addresses inefficiencies in current PET system accreditation methods, introducing a contrast recovery coefficient-based system for reproducibility and reliability. Universal adoption will provide advantages for stakeholders, enabling trusted data comparison across the globe.
A new study published in Frontiers in Human Neuroscience reveals that a visual training program called Perceptual Attention Therapy (PATH) produces rapid improvements in reading, attention, memory, and executive function after concussion. PATH addresses underlying visual timing deficits before strengthening specific cognitive skills.
A prospective multicenter trial validated an improved method for predicting treatment benefits in hormone receptor-positive metastatic breast cancer with bone metastases. Metabolic change assessed by FDG-PET/CT accurately predicted progression-free survival as early as 12 weeks after treatment initiation.
The program provides financial aid and unique clinical experiences to medical students, encouraging them to become community physicians. UCF College of Medicine hopes the program can be used as a national model to address the nation's primary care physician shortage.
A new study found that high levels of psychosocial stress in women are associated with early signs of heart tissue changes, whereas male participants showed no such correlation. The research suggests sex-specific differences in how stress affects cardiovascular health.
A new study led by Concordia researchers found that individuals with coronary artery disease (CAD) have widespread structural changes in their white matter compared to healthy controls. The changes were particularly noticeable in regions critical for cognitive and motor functions.
A study at Technical University of Munich found that AI-simplified CT reports reduced reading time to two minutes and improved patient comprehension. Patients rated the simplified texts as more helpful and informative, with 82% finding them easier to read and understand.
A new report from Northwestern University offers six practical strategies to improve the doctor-patient bedside encounter in an era dominated by AI. By employing these strategies, clinicians can strengthen patient-physician relationships, combat inequities, and reduce burnout, ultimately leading to better patient outcomes.
Researchers developed an AI model that outperforms radiologists in detecting hidden objects on chest scans, particularly for cases of foreign body aspiration. The model achieves high precision and recall rates, helping doctors diagnose complex conditions more reliably.
Researchers developed an AI tool to detect bone loss using CT scans originally taken for other purposes, revealing trends in bone loss across a diverse patient population. The study found that young women had higher bone density than men of the same age, with steeper declines among postmenopausal women.
Researchers analyzed carotid plaque samples from 75 Chinese and 111 US patients, revealing distinct differences in plaque morphology, size, and composition. The study highlights the importance of understanding population-specific variations to develop personalized treatment approaches for cerebrovascular events.