early detection Archives - Amazing Health Advances

Early Detection of Melanoma

The AHA! Team — Fri, 06 Jun 2025 05:23:11 +0000

Georgia M. Beasley, MD, MHSc, via Duke Health – Melanoma can be cured if detected early. Here, Georgia M. Beasley, MD, MHSc, a surgical oncologist at Duke Health, talks about what to look for and how to know if you are at high risk. How to Detect Melanoma Melanoma is the most serious form of skin cancer, responsible for the majority of all skin cancer deaths. Close to 100,000 new melanomas will be diagnosed this year. Fortunately, these cancers are usually curable if detected early. According to Dr. Beasley, patients diagnosed in the earliest stage of melanoma have over a 90% survival rate at five years, while those diagnosed at the most advanced stage have a 20 to 30% survival rate. Early detection is not always easy. Of all the moles in the United States, only one in 20,000 to 200,000 is a melanoma, so searching for an early-stage melanoma is a lot like looking for a needle in a haystack. The commonly recommended “ABCD” detection technique — looking for moles that are asymmetrical, have an irregular border, have uneven color, or a diameter larger than a pencil eraser — is quite helpful in detecting advanced melanomas, but to catch these cancers earlier, it’s important to take additional steps. Understand Your Risk Profile About half of melanomas occur in just 1 to 5% of the population. The average age of people when it is diagnosed is 65. But melanoma is not uncommon even among those younger than 30, said Dr. Beasley. In fact, it’s one of the most common cancers in young adults, especially young women. High-risk groups include people who have: A personal or family history of melanoma (two or more close relatives who have been diagnosed with invasive melanoma) Dysplastic (atypical) moles Numerous moles (generally more than 50) If you have one or more of these traits, regular skin checks may help save your life. Look Beyond Your Moles Many people are told that they have “pre-cancerous” moles, but this is a poor term: dysplastic (or atypical) moles may never progress to melanoma, and instead, are better considered a risk marker for melanoma. At least half of melanomas appear in normal skin. Look for Moles that Don’t Match Everyone’s moles are different, explained Dr. Beasley, so it’s hard to come up with a blanket description of normal moles versus early melanomas. If you see a new mole that looks different than your other (average) moles — a different color, irregular shape, a more pronounced border — you should have that different mole checked by a doctor. Look for Changes in Your Moles Identifying changing moles is one of the keys to early detection. All moles are new at some point, especially in young adults, so a new or enlarged mole is not necessarily a melanoma. However, if you note a changing mole, it is appropriate to seek medical advice. Don’t Rely on Memory If you have had a previous melanoma, dysplastic moles, or numerous moles, Dr. Beasley recommends asking your doctor about total-body photography. Instead of relying on memory to determine whether a mole has changed or is new, Duke dermatologists offer total-body photography to provide a baseline for comparison at future examinations. Total body photography CDs can be used in the clinic and at home to allow for comparisons. Heed Your Own Concerns If you are concerned about an area on your skin, that is enough reason for your doctor to be concerned as well. Don’t hesitate to ask for a second opinion if needed. To read the original article click here.

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The AI Tech That Can Spot Serious Illness Before the Doctor

The AHA! Team — Wed, 05 Mar 2025 06:16:00 +0000

John Jeffay via Israel21c – Lavaa Health’s platform can identify disease and hard-to-diagnose illnesses at the earliest stage, allowing doctors to quickly draw up efficient treatment plans. Meet your GP’s new best friend – artificial intelligence (AI). Lavaa Health, an Israeli startup, watches over all patient data, ready to spot early signs of potential health issues, and uses its vast medical database to identify hard-to-diagnose or rare illnesses. It’s a virtual assistant that works in the background to offer help and alerts, but leaves the physician very much in the driver’s seat, from making the diagnosis to drawing up a treatment plan. The company was founded after a family tragedy. Adam Amitai, Lavaa’s CEO, watched helplessly as his 55-year-old mother-in-law succumbed to ovarian cancer. It had taken a year for the doctors to correctly diagnose her, by which time it was too late. She died eight months later. Amitai doesn’t blame the physicians and says they provided excellent care. But he realized they weren’t exploiting the power of AI to get quicker and more accurate insights. And so he interviewed 200 physicians in the United States, to fully understand how AI could best help them. And he drew on his seven years’ experience as an “offensive cyber officer” in the IDF – where a key challenge was sifting vital details from masses of data. Amitai had also continued to work in intelligence afterwards and had set up an automated trading platform for institutional investors. So, he wasn’t from the world of healthcare, but he recognized that it could benefit from advanced systems that had been developed elsewhere. Handling data more efficiently “I understood there was a big problem with data handling in the healthcare industry,” he tells ISRAEL21c. He saw it when each of his three children were born. Every time, the doctor asked for the family’s medical history. And he saw it with the death of his mother-in-law. He believes AI would have suggested ovarian cancer as a diagnosis much sooner. The main problem is in primary care, the people who are in charge of your health on a daily basis “It’s not the physician’s fault, it’s not the care team fault, they’re doing their best, but they just don’t have the tools,” he says. “The main problem is in primary care, the people who are in charge of your health on a daily basis. They’re reactive instead of proactive. They’re trying to solve a single problem, not your whole health.” And they generally lack the resources to understand what the problem is and to diagnose it correctly. Lavaa’s AI-powered Preventive Care Engine Platform assists the physician by offering evidence-based insights. “We are not allowing the computer to try to automatically detect the conditions. We’re using the accepted worldwide care protocols, but we’re using AI to extract the data,” says Amitai. “Physicians cannot go through all of this data by themselves in the amount of time that they have. It’s just impossible, so this is giving them a huge backup. “The number of parameters for a physician to check and the number of possible diseases is infinite, and time is limited. But computers are really good at matching parameters to diseases. “I realized that technology from the intelligence world already did this, so it was a question of applying it to healthcare.” Prevention, intervention Lavaa is all about prevention and early intervention. Its AI platform can generate questions for a particular patient based on what it sees in their records. It may, for example, ask if a female patient remembers the age at which she had her first period – something that’s relevant for breast cancer, but is never recorded in an EMR (electronic medical record). Or it may send targeted messages, questionnaires, or notifications. It acts as an early warning system, designed to prevent the development of chronic or psychological diseases, and cancer. Lavaa currently looks after over 700,000 patients, all in the US, though the company has plans to expand globally. Amitai estimates the technology has so far saved 1,500 lives. “These are people who had a condition that could have been terminal but caught it on time and we managed to alert the physician, which meant the patients got either the right or better drugs, and better treatment, or a referral to the right place,” he says. Lavaa is not the only such AI solution, but Amitai says the healthcare market is big enough for everybody. Some other companies use AI to both inform and to diagnose – unlike Lavaa – or as a “black box” providing a diagnosis but no explanation of its “thinking.” The company has 12 staff members at its offices in Ra’anana, central Israel, and a team working in the US. Lavaa was founded in 2021, has attracted $5 million in investments. A Series A funding round will be launched later this year. “We want to go global,” Amitai says. “Our solution can work anywhere, and we believe it can improve healthcare around the world.” For more information, click here. To read the original article click here.

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Breast Cancer Could Soon Be Detected Early Using a Blood Test

AHA Publisher — Fri, 22 Nov 2019 08:00:34 +0000

Dr. Ananya Mandal, MD via News Medical-Net – Researchers have found that breast cancer may be successfully detected up to five years before any symptoms appear using a blood test. The results of this land mark study which could mean diagnosis of breast cancer early and treating it more effectively, were presented at the 2019 NCRI Cancer Conference Sunday (3rd November 2019). The team of researchers have found that the body typically mounts an immune response to the oncoming cancer before the clinical signs are detectable. These immune responses could be determined using the blood test, explain the researchers. Researchers at the University of Nottingham (UK) worked on the proteins that were specifically produced by the cancer cells called tumour-associated antigens (TAAs). They wrote that these antigens were specific for the cancer and led to the activation of the immune system that begins to make antibodies against the cancer. The team developed a panel of tumour-associated antigens which were typically created by the breast cancer cells. Then they looked at the blood samples to see if the body had developed autoantibodies against these TAAs. The team that is part of the Centre of Excellence for Autoimmunity in Cancer (CEAC) group at the School of Medicine, University of Nottingham, included 90 breast cancer patients in their pilot study. They took the blood samples from the patients when they were diagnosed with the cancer and then matched them with a control group of 90 women who did not have breast cancer. Then they used a special screening technology called the protein microarray to rapidly look at the blood samples for presence of autoantibodies against 40 TAAs that they had identified to be associated with breast cancer. The autoantibodies were also compared with 27 TAAs that were not associated with breast cancer to rule out bias or confounders. Ms. Daniyah Alfattani, a PhD student in the group, who presented the study results at the NCRI Conference, said in a statement, “The results of our study showed that breast cancer does induce autoantibodies against panels of specific tumour-associated antigens. We were able to detect cancer with reasonable accuracy by identifying these autoantibodies in the blood.” For this study the team identified and created three panels of TAAs against which they would test the autoantibodies. When they had more number of TAAs in a panel, they found that the accuracy of the test improved. They used a panel of five TAAs and breast cancer could be successfully detected in only 29 percent of the samples from the cancer patients. Using this panel 84 percent could be declared cancer-free among the control group. Another panel had seven TAAs and was successful in breast cancer detection in 35 percent cases and certified 79 percent controls as cancer-free. The third panel with nine TAAs could identify 37 percent of the cancers among the breast cancer patients and declared 79 percent cancer-free among the controls. Ms Alfattani added that this was a pilot test and more needed to be done. She said, “We need to develop and further validate this test. However, these results are encouraging and indicate that it’s possible to detect a signal for early breast cancer. Once we have improved the accuracy of the test, then it opens the possibility of using a simple blood test to improve early detection of the disease.” As a next step the team has now recruited 800 patients with breast cancer and autoantibodies from their samples are being tested against a panel of nine TAAs. Ms Alfattani said, “A blood test for early breast cancer detection would be cost effective, which would be of particular value in low and middle income countries. It would also be an easier screening method to implement compared to current methods, such as mammography.” If this works, the team believes that within next half a decade, the test might be available at clinics for screening women from breast cancer. According to Ms Alfattani, “A blood test capable of detecting any of these cancers at an early stage is the over-riding objective of our work.” Dr Iain Frame, CEO of NCRI, in his statement said, “Early diagnosis using simple, non-invasive ways of detecting the first signs of cancer is a key strategic priority for NCRI and something we’d all like to see working in practice. The results from this pilot study for a blood test to detect early breast cancer are promising and build on this research group’s expertise in other cancers, such as lung cancer. It’s obviously early days but we look forward to seeing the results from the larger group of patients that are now being investigated.” Dr Kotryna Temcinaite, from charity Breast Cancer Now, said, “It’s really promising that a simple blood test could in future help clinicians detect autoantibodies that may arise before breast tumours develop. While these are early findings, it’s exciting that testing for these autoantibodies could potentially help detect breast cancer earlier or identify women who may benefit from being monitored more closely.” Another team is also working on detecting early lung cancer among 12,000 Scottish smokers who are at risk of developing lung cancer because. They are using a test called the ELISA (Early CDT-Lung) looking for autoantibodies and a CT scan of the chest every couple of years to check for onset of cancer. Similar work is also being done with colorectal cancers, liver cancers and pancreatic cancers. The latter is particularly difficult to detect early and when detected usually has a poor prognosis. To read the original article click here.

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Movies Can Be Early Detection System for Autism

AHA Publisher — Fri, 15 Nov 2019 08:00:34 +0000

Daniel Ben Tal via Israel21c – Israeli researchers indicate that tracking gaze patterns is measurable, reliable and offers great clinical potential. Researchers at Ben-Gurion University of the Negev have discovered a way to accurately identify nearly half of autism spectrum disorder (ASD) cases – by measuring children’s gaze patterns as they watch movies. In a new study, just published in Autism Research, the researchers demonstrate that children with ASD watch scenes featuring social interactions with significantly more variable gaze patterns than control groups. Children with ASD fixate less on faces in comparison to typically developing children, who observe faces, gestures, body movements and objects that are relevant to the social interaction and its narrative. While typically developing children usually agree on where and when to look at specific locations in a frame, children with ASD exhibit relatively idiosyncratic gaze patterns. Moreover, their gaze patterns are remarkably inconsistent not only between individuals, but also across movie presentations – when children with ASD watch the same movie repeatedly, they have more variable and inconsistent gaze patterns. Abnormal, idiosyncratic gaze patterns were most pronounced when ASD children observed real-life unedited interactions of other children – making the findings particularly relevant to real-life social situations. The largest differences across ASD and control groups were apparent when using a realistic video containing a social interaction between two sisters (two and five years-old) in a messy room with everyday objects. Eye Tracking for Clinical Use “Eye tracking is likely to be one of the first technologies that will be incorporated into clinical use for assessment of ASD symptoms,” explains Prof. Ilan Dinstein, of BGU’s Departments of Psychology and Cognitive and Brain Sciences and director of Israel’s National Autism Research Center,”but it needs to be optimized to identify and quantify specific ASD symptoms.” According to the United States Center for Disease Control (CDC), one in 59 children in the U.S. has ASD. “Taken together, these results demonstrate that ASD children with more severe symptoms exhibit larger gaze idiosyncrasy,” Dinstein says. “This can aid not only in early detection of autism, but also in assessing changes in ASD severity over time and in response to treatments. Such measures, which objectively measure symptoms directly from the child, are critically lacking in today’s clinical trials of autism treatments.” To read the original article click here. For more articles from Israel21c click here.

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Deep-Learning Tech Reveals Personal ID of Cancer Cells

AHA Publisher — Tue, 29 Oct 2019 07:00:36 +0000

Brian Blum via Israel21c – Technion’s computerized pathologist decodes cancer signatures to improve personalized medicine. Just as every handwritten signature is unique, so is every cancerous tumor. Researchers at the Technion-Israel Institute of Technology have now used artificial intelligence and big datato decode the unique signatures of certain cancer cells. (The original scan (left) and the areas where information was extracted (in red and green, right) using the technology developed at the Technion. Photo courtesy of Technion Spokesperson Department) The resulting technology – dubbed a “computerized pathologist” –could significantly boost development of personalized cancer treatments. The researchers worked with digital images from breast-cancer biopsy samples. The new technology, described earlier this summer in the medical journal JAMA, extracts molecular information from the cell shape (morphology) and its environment. “Pathologists we spoke to said it was an impossible task,” explained doctoral student Gil Shamai, who worked with Prof. Ron Kimmel of the Technion’s Faculty of Computer Science and fellow doctoral student Ron Slossberg. “A human pathologist cannot infer the tumor features from its shape because of the sheer number of variables. The good news is that artificial intelligence technologies, and especially deep learning, are capable of doing so. The computer, unlike even the most skilled pathologist, can characterize the cancer with a complex analysis of its morphology.” With the help of image processing and AI tools, the researchers predicted the molecular profile of cancerous cells just by looking at the tissue as it appears on standard biopsy scans. “We succeeded in identifying the ‘signature’ that the cancer leaves in the tissue,” Shamai added. The team had to write its own software code to compare the biopsies it was analyzing with samples of more than 20,000 scans from 5,356 breast cancer patients. Such deep learning systems “require a huge amount of information and obtaining the kind of information required is not easy.” The researchers were then able to map estrogen and progesterone receptors along with other molecular biomarkers. The study focused on breast cancer, but the technology will be relevant to all cancers. “This is a feasibility study,” said Kimmel. “In the first phase, we believe it will be a tool to help doctors make decisions and will later be developed as a real clinical tool.” The research was supported by the Ministry of Science and Technology, the National Science Foundation, the Lorry Lokey Interdisciplinary Center for Life Sciences and Engineering, and Schmidt Futures. Dr. Yoav Binenbaum of Tel Aviv Medical Center and Prof. Ziv Gil of Rambam Medical Center also participated in developing the technology. To read the original article click here. For more articles from Israel21c click here.

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New Blood Test Capable of Detecting Multiple Types of Cancer

AHA Publisher — Sat, 05 Oct 2019 07:00:50 +0000

Dana-Farber Cancer Institute via News Wise – The new test looks for DNA, which cancer cells shed into the bloodstream when they die. In contrast to “liquid biopsies,” which detect genetic mutations or other cancer-related alterations in DNA, the technology focuses on modifications to DNA known as methyl groups. Newswise — A new blood test in development has shown ability to screen for numerous types of cancer with a high degree of accuracy, a trial of the test shows. Dana-Farber Cancer Institute investigators will present the results of the multi-center trial during a session today at the European Society for Medical Oncology (ESMO) 2019 Congress. The test, developed by GRAIL, Inc., uses next-generation sequencing technology to probe DNA for tiny chemical tags (methylation) that influence whether genes are active or inactive. When applied to nearly 3,600 blood samples – some from patients with cancer, some from people who had not been diagnosed with cancer at the time of the blood draw – the test successfully picked up a cancer signal from the cancer patient samples, and correctly identified the tissue from where the cancer began (the tissue of origin). The test’s specificity – its ability to return a positive result only when cancer is actually present – was high, as was its ability to pinpoint the organ or tissue of origin, researchers found. The new test looks for DNA, which cancer cells shed into the bloodstream when they die. In contrast to “liquid biopsies,” which detect genetic mutations or other cancer-related alterations in DNA, the technology focuses on modifications to DNA known as methyl groups. Methyl groups are chemical units that can be attached to DNA, in a process called methylation, to control which genes are “on” and which are “off.” Abnormal patterns of methylation turn out to be, in many cases, more indicative of cancer – and cancer type – than mutations are. The new test zeroes in on portions of the genome where abnormal methylation patterns are found in cancer cells. “Our previous work indicated that methylation-based assays outperform traditional DNA-sequencing approaches to detecting multiple forms of cancer in blood samples,” said the study’s lead author, Geoffrey Oxnard, MD, of Dana-Farber. “The results of the new study demonstrate that such assays are a feasible way of screening people for cancer.” In the study, investigators analyzed cell-free DNA (DNA that had once been confined to cells but had entered the bloodstream upon the cells’ death) in 3,583 blood samples, including 1,530 from patients diagnosed with cancer and 2,053 from people without cancer. The patient samples comprised more than 20 types of cancer, including hormone receptor-negative breast, colorectal, esophageal, gallbladder, gastric, head and neck, lung, lymphoid leukemia, multiple myeloma, ovarian, and pancreatic cancer. The overall specificity was 99.4%, meaning only 0.6% of the results incorrectly indicated that cancer was present. The sensitivity of the assay for detecting a pre-specified high mortality cancers (the percent of blood samples from these patients that tested positive for cancer) was 76%. Within this group, the sensitivity was 32% for patients with stage I cancer; 76% for those with stage II; 85% for stage III; and 93% for stage IV. Sensitivity across all cancer types was 55%, with similar increases in detection by stage. For the 97% of samples that returned a tissue of origin result, the test correctly identified the organ or tissue of origin in 89% of cases. Detecting even a modest percent of common cancers early could translate into many patients who may be able to receive more effective treatment if the test were in wide use, Oxnard remarked. To read the original article click here.

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