Heman Bekele has just been named Time’s 2024 Kid of the Year.
S 15, is already spending part of every weekday working in a lab at the Johns Hopkins Bloomberg School of Public Health in Baltimore, hoping to bring his dream to fruition. ‘.
Last year NPR interviewed Heman Bekele about his invention of a soap to fight skin cancer. He was motivated by his childhood in Ethiopia: He saw people working in the sun and thought of health risks.
Posted in biotech/medical, health, robotics/AI | Leave a Comment on Advanced Skin Disease Diagnosis and Treatment Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance
【Advanced Skin Disease Diagnosis and Treatment: Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance】 Full article: (Authored by Noshin Un Noor, et al., from World University of Bangladesh, Bangladesh.)
Skin_diseases are a major global health concern, encompassing a wide range of conditions with varying severity. Prompt and precise diagnosis is critical for effective treatment. However, traditional methods often rely on dermatologists, creating disparities in access to care. This study creates and assesses a highly accurate Convolutional Neural Network (CNN) model that can use digital photos of skin lesions to diagnose a variety of skin conditions, and looks into how well various CNN architectures and pre-trained models may increase the precision and effectiveness of diagnosing skin conditions.
Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated skin disease diagnostic method. The work uses preprocessing methods like scaling, normalization, and augmentation to improve model robustness using the DermNet dataset, which consists of 19,500 pictures from 23 disease categories. TensorFlow and Keras were used to create a unique CNN architecture, which produced an impressive accuracy of 94.65%. Metrics like precision, recall, and F1-score were used to validate the model’s performance, showing that it outperformed more conventional machine learning techniques like SVM and KNN. The system incorporates patient-reported symptoms in addition to diagnosis to provide a comprehensive approach to health support, allowing for remote accessibility and tailored therapy suggestions. This work recognizes issues like dataset variability and processing needs while showcasing the revolutionary potential of AI in dermatology. In order to improve model interpretability and clinical integration, future possibilities include dataset extension, real-world validation, and the use of explainable AI.
Skin Disease Diagnosis, Dermatological Image Analysis, Medical Image Classification, Convolutional Neural Networks (CNNs), Healthcare Accessibility, Deep Learning Applications, DermNet Dataset
The Automated Intimate Partner Violence Risk Support System (AIRS) utilizes clinical history and radiologic data to pinpoint patients seen in the emergency room who may be at a risk for intimate partner violence (IPV). Developed over the past five years, AIRS has been rolled out to the Brigham and Women’s Hospital’s Emergency Rooms in Boston as well as surrounding primary care sites. Currently, the tool has been validated at the University of California-San Francisco Medical Center and is being evaluated by the Alameda Health System for its role in clinical workflow.
“Data labeling quality is a huge concern—not just with intimate partner violence care, but in machine learning for healthcare and machine learning, broadly speaking,” says cofounder Irene Chen. “Our hope is that with training, clinicians can be taught how to spot intimate partner violence—we are hoping to find a set of cleaner labels.”
Mirror life, a concept involving synthetic organisms with reversed molecular structures, carries significant risks despite its potential for medical advancements.
Experts warn that mirror bacteria could escape natural biological controls, potentially evolving to exploit resources in ways that disrupt ecosystems and pose unforeseen dangers to the environment and public health.
Mirror Life
Tires and degrading garbage shed tiny pieces of plastic into the air, creating a form of air pollution that UC San Francisco researchers suspect may be causing respiratory and other illnesses.
A review of some 3,000 studies implicates these particles in a variety of serious health problems. These include male and female infertility, colon cancer and poor lung function. The particles also may contribute to chronic pulmonary inflammation, which can increase the risk of lung cancer.
“These microplastics are basically particulate matter air pollution, and we know this type of air pollution is harmful,” said Tracey J. Woodruff, Ph.D., MPH, a professor of obstetrics, gynecology and reproductive sciences at UCSF.
Over the past two years, the U.S. Centers for Disease Control and Prevention (CDC) has issued Travel Health Advisories focused on measles outbreaks.
These advisories highlight where there is an active health risk when people visit the highlighted countries.
On February 21, 2025, the CDC reissued a Level 1, Practice Usual Precautions, alert for 57 countries. This CDC list does not integrate the Region of the Americas, with numerous countries reporting 537 measles outbreaks this year.
A research team has identified different subtypes of white matter (WM) astrocytes, including a unique type with the ability to multiply and potentially aid in brain repair. Using single-cell RNA sequencing and spatial transcriptomics, the scientists mapped astrocyte diversity across different brain regions and species, providing the first detailed molecular profile of WM astrocytes.
The team was led by Dr. Judith Fischer-Sternjak from Helmholtz Munich and Ludwig-Maximilians-Universität (LMU) München, alongside Prof. Magdalena Götz from Helmholtz Munich, LMU and the Munich Cluster for Systems Neurology (SyNergy). The research is published in the journal Nature Neuroscience.
Unveiling white matter astrocyte diversity Astrocytes, known for their crucial role in supporting neurons and maintaining brain health, have been predominantly studied in gray matter (GM), which is involved in information processing. However, white matter astrocytes, which support long-range neural connections, remain poorly understood. This study fills a major knowledge gap by showing that WM astrocytes are not a uniform population but consist of distinct subtypes with specialized roles.
Scientists still don’t know how microplastics impact human health, but they do have ideas for stopping their spread.
A research team led by Prof. Jiang Changlong from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed an innovative dual-mode sensing platform using upconversion nanoparticles (UCNPs). This platform integrates fluorescence and colorimetric methods, offering a highly sensitive and low-detection-limit solution for bilirubin detection in complex biological samples.
The findings, published in Analytical Chemistry, offer a new technological approach for the early diagnosis of jaundice.
Jaundice is a critical health issue in neonates, affecting 60% of newborns and contributing to early neonatal mortality. Elevated free bilirubin levels indicate jaundice, with healthy levels ranging from 1.7 μM to 10.2 μM in healthy individuals. Concentrations below 32 μM typically don’t show classic symptoms. Rapid and accurate detection of bilirubin in neonates is critical.
Microplastics have been found almost everywhere that scientists have looked for them. Now, according to research published in Environment & Health, these bits of plastic—from 1 to 62 micrometers long—are present in the filtered solutions used for medical intravenous (IV) infusions. The researchers estimate that thousands of plastic particles could be delivered directly to a person’s bloodstream from a single 8.4-ounce (250-milliliter) bag of infusion fluid.
In clinical settings, IV infusions are packaged in individual plastic pouches and deliver water, electrolytes, nutrients or medicine to patients. The base of these infusions is a saline solution that contains filtered water and enough salt to match the content of human blood. Research from the 1970s suggests IV fluid bags can contain solid particles, but few scientists have followed up on what those particles are made of.
Researchers Liwu Zhang, Ventsislav Kolev Valev and colleagues suspected that these particles could be microplastics that—upon infusion —would enter the recipient’s bloodstream and potentially cause negative health effects. So, they set out to analyze the types and amounts of particles in commercial IV fluid bags.
