Search Results for “artificial intelligence” – Page 11 – media

Customizable AI Tool Helps Pathologists Identify Diseased Cells

Pathologists are tasked with examining body fluids or tissues to diagnose diseases, a process that involves distinguishing rare disease-indicating cells from thousands of normal cells under a microscope. This skill requires extensive training. Artificial intelligence (AI) can assist by learning to differentiate between healthy and diseased cells from digital pathology images. However, traditional AI tools, once trained, lack flexibility. They are designed for specific tasks, such as identifying cancer cells in one organ but not another, and might not align perfectly with a pathologist’s specific needs in different scenarios. Now, a collaborative team of computer scientists and physicians has developed a new AI tool that not only identifies diseased cells but also adapts to a pathologist’s requirements. Developed at Stanford Medicine (Stanford, CA, USA), the tool, named nuclei.io, functions like a human assistant that evolves with feedback. Starting with the basic function of recognizing different cell types by their nuclei, ...
- Source: drugdu
- 96
- June 28, 2024
Lilly joins fellow pharma giants in OpenAI partnership

Eli Lilly has joined a growing list of pharma companies to partner with OpenAI, as it seeks to develop new treatments for drug-resistant pathogens. The collaboration will utilise the generative artificial intelligence (genAI) from OpenAI to come up with new solutions for microbial infections. Lilly didn’t specify the exact details of how OpenAI’s technology will be used, or any financial terms of the deal. Lilly joins Sanofi and Moderna, who have both unveiled partnerships with the genAI platform OpenAI this year. Last month, Sanofi announced that it was partnering with Formation Bio and OpenAI to harness AI to expedite drug development. On the other hand, Moderna has incorporated ChatGPT into an internal messaging platform called mChat, to harness data analytics, and use image generation, and dose selection. This new collaboration with OpenAI builds on Lilly’s commitment to tackle antimicrobial resistance (AMR). The pharma giant previously contributed $100m to the AMR ...
- Source: drugdu
- 108
- June 28, 2024
Customizable AI Tool Helps Pathologists Identify Diseased Cells

Pathologists are tasked with examining body fluids or tissues to diagnose diseases, a process that involves distinguishing rare disease-indicating cells from thousands of normal cells under a microscope. This skill requires extensive training. Artificial intelligence (AI) can assist by learning to differentiate between healthy and diseased cells from digital pathology images. However, traditional AI tools, once trained, lack flexibility. They are designed for specific tasks, such as identifying cancer cells in one organ but not another, and might not align perfectly with a pathologist’s specific needs in different scenarios. Now, a collaborative team of computer scientists and physicians has developed a new AI tool that not only identifies diseased cells but also adapts to a pathologist’s requirements. Developed at Stanford Medicine (Stanford, CA, USA), the tool, named nuclei.io, functions like a human assistant that evolves with feedback. Starting with the basic function of recognizing different cell types by their nuclei, ...
- Source: drugdu
- 145
- June 27, 2024
Portable Device Analyzes White Blood Cell Activity to Monitor Cancer Patients’ Health

Chemotherapy and similar treatments aimed at eliminating cancer cells often adversely affect patients’ immune cells. Each year, this results in tens of thousands of cancer patients suffering from weakened immune systems, making them susceptible to potentially fatal infections. Physicians are tasked with balancing the dosage of chemotherapy—enough to kill cancer cells but not so much as to dangerously reduce the patient’s white blood cell count, leading to neutropenia. This condition not only impacts health but can also lead to social isolation between chemotherapy sessions. Traditionally, monitoring of white blood cells has been limited to blood tests. Now, a new at-home white blood cell monitor offers doctors the ability to remotely monitor their patients’ health more comprehensively. This device, which avoids blood draws, uses light to scan the skin at the top of the fingernail and employs artificial intelligence (AI) to identify critically low levels of white blood cells. Based on ...
- Source: drugdu
- 121
- June 25, 2024
AI-Powered Blood Test Predicts Parkinson’s Seven Years before Symptoms Appear

Parkinson’s disease is currently the fastest-growing neurodegenerative disorder worldwide, affecting nearly 10 million people globally. It is a progressive disease caused by the deterioration and death of nerve cells in a part of the brain known as the substantia nigra, which is essential for movement control. These nerve cells diminish or become damaged, losing their ability to produce a crucial chemical, dopamine, often due to the accumulation of a protein called alpha-synuclein. Presently, treatments for people with Parkinson’s, such as dopamine replacement therapy, are initiated after symptoms like tremors, slow movements, gait issues, and memory problems have already appeared. However, there is a consensus among researchers that early prediction and diagnosis could lead to discoveries of treatments capable of slowing or halting the progression of Parkinson’s by protecting dopamine-producing brain cells. Now, a simple blood test employing artificial intelligence (AI) can predict the onset of Parkinson’s up to seven years ...
- Source: drugdu
- 127
- June 25, 2024
Self-Taught AI Tool Diagnoses and Predicts Severity of Common Lung Cancer

A computer program powered by artificial intelligence (AI) and trained on nearly half a million tissue images can effectively diagnose cases of adenocarcinoma, the most prevalent type of lung cancer. The computer program developed and tested by researchers at NYU Langone Health (New York, NY, USA) provides an unbiased, detailed, and reliable second opinion for patients and oncologists regarding the presence of the cancer and the possibility and timing of its return, also known as its prognosis. This is because the program incorporates structural features of tumors from 452 adenocarcinoma patients, who are among the more than 11,000 patients in the U.S. National Cancer Institute’s Cancer Genome Atlas. Importantly, the program operates independently and is “self-taught,” deciding by itself which structural features are most critical for assessing the severity of the disease and its impact on tumor recurrence. In their research, the algorithm, known as histomorphological phenotype learning (HPL), successfully ...
- Source: drugdu
- 97
- June 14, 2024
US researchers develop AI liquid biopsy test to help identify lung cancer earlier

Researchers from the Johns Hopkins Kimmel Cancer Center and other institutions have developed and validated a liquid biopsy test using artificial intelligence (AI) to help identify lung cancer earlier. The new study published in Cancer Discovery demonstrated that the new blood test could help accelerate lung cancer screening while reducing death rates. Currently the leading cause of global cancer incidence and death worldwide, lung cancer accounts for an estimated two million diagnoses and 1.8 million deaths annually. For the last five years, researchers have developed a test to detect patterns of DNA fragments found in patients with lung cancer. Participants with and without cancer who met the criteria for low-dose computed tomography (CT) were recruited to receive the blood test to determine which patients were most at risk and would benefit from a follow-up CT screening to help overcome issues regarding appointments, such as the time it takes to arrange ...
- Source: drugdu
- 105
- June 14, 2024
Novel AI-Powered Method for Tissue Analysis Improves Understanding of Disease Pathology

Scientists at Brown University (Providence, RI, USA) and the University of Michigan (Ann Arbor, MI, USA) have created a groundbreaking computational technique to examine complex tissue data, potentially revolutionizing our understanding of diseases and their treatment. The method, known as Integrative and Reference-Informed tissue Segmentation (IRIS), utilizes machine learning and artificial intelligence to provide biomedical researchers with accurate insights into tissue development, disease pathology, and tumor structuring. IRIS employs spatially resolved transcriptomics (SRT) data and incorporates single-cell RNA sequencing data as a reference. This approach allows for the simultaneous examination of multiple tissue layers and accurately identifies different regions with exceptional computational speed and precision. In contrast to traditional methods that offer averaged data from tissue samples, SRT delivers a much more detailed perspective, locating thousands of specific points within a single tissue section. Handling vast and complex datasets has always posed significant challenges, and IRIS addresses these by using ...
- Source: drugdu
- 137
- June 13, 2024
AI Tool Predicts Cancer Patients’ Response to Immunotherapy

Immune checkpoint inhibitors are a form of immunotherapy drug that enables immune cells to target and destroy cancer cells. At present, the Food and Drug Administration has approved two predictive biomarkers for identifying patients who might benefit from immune checkpoint inhibitors. The first biomarker is tumor mutational burden, which measures the number of mutations in the DNA of cancer cells. The second biomarker is PD-L1, a protein found on tumor cells that inhibits the immune response and is targeted by some immune checkpoint inhibitors. However, these biomarkers are not always reliable in predicting a patient’s response to immune checkpoint inhibitors. Recent machine-learning models utilizing molecular sequencing data have demonstrated potential in predicting responses, but this data is costly and not routinely collected. Researchers have now created an artificial intelligence (AI) tool that uses standard clinical data, such as results from a basic blood test, to predict if a patient’s cancer ...
- Source: drugdu
- 87
- June 7, 2024
International KCL research project to develop SMARTdrugs for aggressive cancers

The platform will be used to diagnose and treat cancers, including lung and brain tumours A new international study led by King’s College London (KCL) researchers is developing a radiotheranostic platform called SMARTdrugs for the diagnosis and treatment of aggressive forms of cancer. With partners in Munich, Zurich, San Sebastian and Utrecht, the study has been awarded a Pathfinder Open Grant of nearly €4m from the European Innovation Council. Aggressive cancers such as lung and brain tumours occur when the growth rate is impacted by the genetic makeup of the tumour and the rate at which the cells are dividing. Researchers aim to create supramolecular compounds as an alternative to the current standard of attaching radionuclides directly to drug molecules to allow clinicians to visualise key signatures of tumours using medical imaging systems. The supramolecular compounds will have greater control over their size, shape and other biochemical properties than other ...
- Source: drugdu
- 68
- June 5, 2024

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