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Obstetrics/Gynecology


Woman, 22, who says gynecologist denied her of tube tying procedure speaks out

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The woman who recently sparked a conversation on TikTok about tube tying, is speaking out after she claimed a gynecologist told her she couldn't have the procedure done because she could change her mind and meet "Mr. Olivia Downs, 22, turned to the video-sharing app on Wednesday, June 15, to relay what she says a female gynecologist told her during a tubal ligation consultation in Springfield, Massachusetts. Tubal ligation is a sterilization procedure that's done to prevent sperm from meeting an egg. Not all doctors are willing to carry out the procedure because it can sometimes be impossible or extremely difficult to reverse. It also comes with fertility risks if a woman does in fact change her mind. In her consultation reenactment, Downs said the doctor repeatedly told her, "no" because the sterilization procedure is "permanent" and instead was given a brochure for a copper intrauterine device (IUD), which has the same efficacy rate, but isn't what she asked for. Downs' TikTok video has surpassed 2.1 million views and has generated more than 444,900 likes and 6,900 comments. Olivia Downs, a 22-year-old student and orthodontic assistant from Massachusetts, shared a video about an OB/GYN appointment she had in June 2022, where a gynecologist reportedly denied her request for a tubal ligation procedure because she could change her mind and meet'Mr. Downs, who is a full-time neuroscience student and orthodontic assistant, told Fox News Digital that she never planned on going viral. "Honestly I was shocked this video went viral," Downs said. "I sort of posted it as a joke and didn't expect it to go anywhere, but it blew up." She continued, "I didn't realize how big of an issue this was or how many women have been in a similar situation and their frustrations, so it's been really eye-opening, honestly." Downs said people have voiced opposition to tubal ligation because they think that a woman could eventually regret having the procedure. Obstetrician-gynecologists are medical doctors who treat patients and advise them on various reproductive treatments and procedures, including tubal ligation, also known as tube tying. Downs said she's heard from critics who have called women "lazy and immature" or are "wasting our privilege" if they don't intend on having kids. She wants those critics to stop and listen to a woman's reasoning as to why they don't want to have children before getting defensive and resorting to name-calling, Downs explained. "Even if someone did change their minds after the procedure, there are always options like getting it reversed, IVF, or surrogacy," Downs continued. There are tons of children in our foster care system waiting to be adopted into a stable home, and it's such a wonderful alternative."


A Straightforward HPV16 Lineage Classification Based on Machine Learning

#artificialintelligence

Human Papillomavirus (HPV) is the causal agent of 5% of cancers worldwide and the main cause of cervical cancer and it is also associated with a significant percentage of oropharyngeal and anogenital cancers. More than 60% of cervical cancers are caused by HPV16 genotype, which has been classified into lineages (A, B, C, and D). Lineages are related to the progression of cervical cancer and the current method to assess lineages is by building a Maximum Likelihood Tree (MLT); which is slow, it cannot assess poor sequenced samples, and annotation is done manually. In this study, we have developed a new model to assess HPV16 lineage using machine learning tools. A total of 645 HPV16 genomes were analyzed using Genome-Wide Association Study (GWAS), which identified 56 lineage-specific Single Nucleotide Polymorphisms (SNPs). From the SNPs found, training-test models were constructed using different algorithms such as Random Forest (RF), Support Vector Machine (SVM), and K-nearest neighbor (KNN). A distinct set of HPV16 sequences (n = 1,028), whose lineage was previously determined by MLT, was used for validation. The RF-based model allowed a precise assignment of HPV16 lineage, showing an accuracy of 99.5% in the known lineage samples. Moreover, the RF model could assess lineage to 273 samples that MLT could not determine. In terms of computer consuming time, the RF-based model was almost 40 times faster than MLT. Having a fast and efficient method for assigning HPV16 lineages,...


The Download: Abortion pill access, and Europe's ethical AI

MIT Technology Review

If the US Supreme Court overturns Roe v. Wade, the 1973 legal decision that enshrined abortion as a constitutional right, parts of the country will be ready to plunge into a reproductive-rights dark age in which doctors are forbidden from providing any abortions, in some states even in cases of rape, incest, or a fetus with genetic abnormalities. But there's still one huge loophole: most of these pending state laws exempt the person seeking the abortion from any penalties. The likely result is an increase in the number of people ending pregnancies at home using so-called abortion pills. MIT Technology Review spoke to medical professionals and reproductive-rights lawyers to find out how the abortion pills work, where to get them, and what the risks are of using them without a doctor's care. "Obviously, expensive digital images of monkeys are going to improve the world immensely."


How visual-based AI is evolving across industries

#artificialintelligence

Artificial Intelligence is transforming the business world as a whole with all its applications and potential, with visual-based AI being capable of digital images and videos. Visual-based AI, which refers to computer vision, is an application of AI that is playing a significant role in enabling a digital transformation by enabling machines to detect and recognize not just images and videos, but also the various elements within them, such as people, objects, animals and even sentiments, emotional and other parameters-based capabilities to name a few. Artificial intelligence is now further evolving across various industries and sectors. Transport: Computer vision aids in a better experience for transport, as video analytics combined with Automatic number plate recognition can help in tracking and tracing violators of traffic safety laws (speed limits and lane violation etc.) and stolen or lost cars, as well as in toll management and traffic monitoring and controlling. Aviation: Visual AI can help in providing prompt assistance for elderly passengers and for those requiring assistance (physically challenged, pregnant women etc.); it can also be useful in creating a new "face-as-a-ticket" option for easy and fast boarding for passengers, in tracking down lost baggage around the airport as well as in security surveillance on passengers and suspicious objects (track and trace objects and passengers relevant to it).


Amazon Alexa can now answer common questions around menopause

Daily Mail - Science & tech

Amazon's Alexa voice assistant is already a fount of knowledge on health topics ranging from the symptoms of chicken pox to how to relive a migraine. Now Amazon has teamed up with independent website Menopause Matters to provide answers to some of the most commonly asked questions around menopause. Alexa users in the UK can ask questions including'What treatments are available for the menopause?', 'What is perimenopause?', and'What are the benefits or risks of Hormone Replacement Therapy for menopause?' The news comes amid warnings that women going through the menopause are often mis-diagnosed with depression, because GPs do not know all the symptoms.


The Download: Meta's AI giveaway, and abortion clinic data tracking

MIT Technology Review

Open to ideas: Meta's AI lab has created a massive new language model, and in an unprecedented move for Big Tech, it is giving it away to researchers--together with details about how it was built. Large language models--powerful programs that can generate paragraphs of text and mimic human conversation--have become one of the hottest trends in AI in the last couple of years. But they have deep flaws, parroting misinformation, prejudice, and toxic language. Wider scrutiny: Meta's decision represents the first time that a fully trained large language model will be made available to any researcher who wants to study it. In theory, putting more people to work on the problem should help.


Leeds breast imaging service adds Densitas AI for quality control of mammograms - RAD Magazine

#artificialintelligence

The breast imaging service at Leeds Teaching Hospitals NHS Trust is the first in the UK to introduce an AI technology from Densitas that evaluates the technical quality of mammograms. The Canadian software company has worked to customise the intelliMammo software to meet the department's needs and the image quality standards required by the NHS Breast Screening Programme. The technology will be implemented in the screening and symptomatic breast services to provide mammographers with instant feedback and AI-generated positioning information. This means that any quality issues are flagged at the patient's appointment, which should reduce recall rates and enhance the accuracy of the image interpretation. Director of breast screening Dr Nisha Sharma said: "Using AI will make a real difference to the quality of our breast screening programme and ultimately to the health outcomes of women in Leeds. We are delighted to collaborate with Densitas and build on this foundation for future developments that will improve breast care."


Mitigating The Effects Of Gender Bias In Clinical Trials - Zenger News

#artificialintelligence

It is an open secret that women are underrepresented in clinical trials of new pharmaceuticals and other medical treatments. This has a significant impact on the female half of the population. A new article in the Journal of the American Medical Informatics Association by computer scientists at the Technion-Israel Institute of Technology, in collaboration with Plia Gillis of Tel Aviv University and Eric Horvitz of Microsoft Research, describes the problems caused by this bias and presents a machine-learning remedy. "Nowadays, we know that different population groups react differently to a given treatment – in particular, women can have a different reaction than men to a treatment," said Shunit Agmon, the PhD candidate who conducted the research with Technion alumna and visiting professor Kira Radinsky. "For example, Zolpidem, a drug used to treat sleeping problems, clears more slowly in women and therefore it is important to prescribe a smaller dose for women than for men -- which was discovered only after the drug was released to the market," said Agmon.


As a science journalist I'm reconsidering having kids. I'm not the only one

#artificialintelligence

"I'm running out of time, but I'm also not gonna be like, 'I'm having a baby for the sake of having a baby,'" said the younger of the two. "One thing I would recommend," replied the older woman, "if it's an option: freeze your eggs." As a woman, you get to a certain age and babies – hypothetical, expected, realised – suddenly seem ubiquitous: in friendship circles, on social media, in targeted advertising for pregnancy tests and public health messages. But for women of my generation, the decision whether to have children feels more existentially fraught and morally complex than ever before. I have always wanted kids. I have always felt an uncomplicated joy at the chubbiness of babies' limbs and the infectiousness of a child's laughter.


Google wants to use AI to cut the maternal mortality rate by half

#artificialintelligence

Its other two initiatives center on developing software that turn mobile phones into health tools. The first, an extension of Google's past work using artificial intelligence to detect diabetic retinopathy from specialty retinal scans, uses a cellphone camera to take a picture of a person's eye from which it can detect signs of diabetic retinopathy. The third project revolves around software that can turn a smartphone into a stethoscope. All of these ideas seek to position Google at the forefront of both artificial intelligence in healthcare and the future of health at home. Whether these inventions will really deliver on that promise is up for debate.