AI outperforms human doctors in prostate cancer detection with 84% accuracy.
Avenda Health's AI technology recently cleared by FDA.
UCLA study shows AI tool creates 3D cancer estimation map from patient data for personalized treatment plans.
Artificial Intelligence (AI) is revolutionizing cancer detection and treatment, outperforming human doctors in accuracy and efficiency.
According to a study conducted at the University of California, Los Angeles (UCLA), an AI tool identified prostate cancer with 84% accuracy compared to 67% accuracy for cases detected by physicians.
The AI technology, developed by Avenda Health in California and recently cleared by the US Food and Drug Administration, creates a 3D cancer estimation map from patient data to optimize their cancer care and personalize treatment plans.
One of the study's participants, Joshua Trachenberg, a UCLA professor and prostate cancer patient, underwent experimental therapy using Unfold AI technology to avoid radical prostatectomy. Radical prostatectomy is a surgical procedure that removes the entire gland and can result in side effects such as incontinence and impotence.
Unfold AI gives hope for future prostate cancer treatment, enabling therapies that don't put men through the
UCLA study found that an AI tool identified prostate cancer with 84% accuracy compared to 67% accuracy for cases detected by physicians.
Unfold AI creates a 3D cancer estimation map from patient data to optimize their cancer care and personalize treatment plans.
Joshua Trachenberg, a UCLA professor and prostate cancer patient, underwent experimental therapy using Unfold AI technology to avoid radical prostatectomy.
Unfold AI gives hope for future prostate cancer treatment, enabling therapies that don’t put men through the ‘meat grinder’ of full-gland removal and its side effects.
Accuracy
No Contradictions at Time
Of
Publication
Deception
(50%)
The article is moderately deceptive. It claims that an AI tool identified prostate cancer with 84% accuracy compared to 67% for physicians, making it seem like a significant improvement. However, the actual increase in accuracy is only by 17%, which might not be as impressive as it initially appears. The article also does not mention any potential limitations or drawbacks of the AI tool beyond privacy concerns and cost, giving readers an incomplete picture of its effectiveness.
...making it seem like a significant improvement. However, the actual increase in accuracy is only by 17%.
The AI tool identified prostate cancer with 84% accuracy...
UCLA study found that an AI tool identified prostate cancer with 84% accuracy compared to 67% accuracy for cases detected by physicians.
AI creates a 3D cancer estimation map from patient’s prostate cancer information and results.
Unfold AI helps optimize personalized cancer care by determining if a patient is better suited for focal therapy or more radical therapy.
AI technology gives hope for future prostate cancer treatment, enabling therapies that don’t put men through radical prostatectomy side effects.
Accuracy
No Contradictions at Time
Of
Publication
Deception
(80%)
The article makes several statements that could be considered sensational or selectively reporting. The title states that the AI detects cancer with '17 more accuracy' than doctors, but the study only reports an 18% difference in accuracy. Additionally, the article focuses on this one study and does not mention any potential limitations or drawbacks of using AI for cancer detection. These practices could be misleading to readers.
The AI tool identified prostate cancer with 84% accuracy – compared to 67% accuracy for cases detected by physicians.
Based on these findings, the AI could lead to more accurate diagnoses and more targeted treatments, reducing the need for full-gland removal and the side effects that can come with it.
Artificial intelligence is outpacing doctors when it comes to detecting a common cancer in men.
Fallacies
(95%)
There are no formal fallacies present in the article. However, there is an appeal to authority and a slight overgeneralization of AI's capabilities in healthcare. The author highlights the success of an AI tool in detecting prostate cancer with greater accuracy than doctors but does not mention any potential limitations or drawbacks of the technology.
According to a press release from the university, an AI tool identified prostate cancer with 84% accuracy compared to 67% accuracy for cases detected by physicians.
Researchers at the University of British Columbia have created an artificial intelligence that can identify a subset of endometrial cancer patients at higher risk of recurrence or death from disease.
Endometrial cancer is the most common gynecological cancer globally and the fourth-most common cancer for people assigned female at birth.
Endometrial cancer cases are on the rise and in a decade or so, they will likely be the second most common cancer after breast cancer.
The AI has been able to flag higher-risk cancers, which is something oncologists are not able to do with existing diagnostic tools.
Endometrial cancer and liver cancer are the only cancers in Canada where the rate patients die from the disease is slowly rising.
The rise in endometrial cancer cases is partially attributed to people living longer, bodies being overall heavier, and fewer people getting hysterectomies than they used to.
"Scientists in San Francisco are using AI to find the best ways to treat cancer."
"Dr. Deepak Srivastava believes this approach will save lives."
"Gladstone Institutes are focusing on skin cancer and colorectal cancer for this research."
'We will be able to take somebody's cancer, that so far has been untreatable, and be able to engineer their own immune cells in ways that it will specifically kill their cancer cell.' - Dr. Deepak Srivastava
'My hope is that over a five-year period, we learned enough that we can design new types of clinical trials.' - Dr. Deepak Srivastava
'Gladstone Institutes received a $5 million grant from the Biswas Family Foundation for this research.'
Accuracy
Scientists in San Francisco are using AI to find the best ways to treat cancer.
AI could lead to more accurate diagnoses and targeted treatments.
Gladstone Institutes received a $5 million grant for this research.
Deception
(100%)
None Found At Time Of
Publication
Fallacies
(95%)
The article contains some instances of appeals to authority fallacy, but overall the author's statements are factual and do not contain any major logical fallacies. The author is reporting on the research being done by scientists at the Gladstone Institutes and their use of artificial intelligence in cancer treatment.
] For the first time, we are going to be able to use artificial intelligence to be able to do millions, if not billions, of experiments. [
We will be able to take somebody’s cancer, that so far has been untreatable, and be able to engineer their own immune cells in ways that it will specifically kill their cancer cell.
My hope is that over a five-year period, we learned enough that we can design new types of clinical trials.
Scientists are using AI and ML algorithms for analyzing genomics data, predictive modelling, and precision oncology.
"Dinesh Gupta stated that AI and ML improve accuracy, efficiency, and timeliness of cancer detection leading to better patient outcomes and reduced healthcare costs."
AIIMS in Delhi launched an AI system trained on 500,000 radiological and histopathological images for breast and ovarian cancer detection.
"Melissa Fullwood's team developed Chromatin Interaction Neural Network (ChINN) to predict chromatin interactions using DNA sequences for drug target identification."
New AI-ML tools are available for cancer pathology, histology analysis, imaging results, and circulating tumour nucleic acids analysis.
"Gupta emphasized the role of machine learning in multi-omics data combining genomes, transcriptomes, proteomes, epigenomes and metabolomes for a comprehensive understanding of cancer biology."
Researchers at Indian Institute of Technology Dharwad identified five novel lung cancer cell clusters using multi-omics-based classification.
"Scientists from Institute of Bioinformatics and Biotechnology Manipal and Kidwai Cancer Institute Bangalore reported different population-specific molecular signatures of ovarian cancer using multi-omics data."
"Chad Creighton highlighted the importance of proteomics in integrating multi-omics data for a complete molecular picture of cancer, revealing cancer molecular subtypes not identified by transcriptomics."
