#Clinical applications

[purplewildchrysanthemum]

Common Chrysanthemum and Wild Chrysanthemum: Differences in Detoxifying Ability and Therapeutic Effects

The picture description: Huangshan Gongju is a kind of chrysanthemum tea produced in Huangshan area, Anhui Province, China. It enjoys a high reputation for its fine quality and rich aroma. With the functions of clearing away heat and detoxifying, regulating the liver and improving eyesight, moisturizing the lungs and relieving cough, it is one of the traditional healthy drinks in China. It is…

[livingwellnessblog]

Exploring the Nexus of Mindfulness, Self-Compassion, and Emotion Regulation in Borderline Personality Disorder (BPD) Treatment

Mindfulness interventions encompass a diverse array of techniques that cultivate present-moment awareness, emotional regulation, and self-compassion.

Emotion Regulation, Mindfulness, and Self-Compassion in Borderline Personality Disorder (BPD) How do emotion regulation difficulties manifest within the spectrum of BPD symptoms? To what extent does the deficit in mindful awareness contribute to emotional dysregulation in BPD? How does self-compassion mitigate the impact of self-criticism and negative affect in BPD? What are the potential…

[interviewhelps]

Top 25 Job Interview Questions for Biomedical engineer

Here are the Top 25 Job Interview Questions for Biomedical engineer Can you tell us about your educational background and how it relates to biomedical engineering? Can you describe a project you have worked on that you are particularly proud of and why? How do you keep up with advancements in technology and the biomedical engineering industry? Can you explain your understanding of the different…

[taradactyls]

Something I love about how Pride and Prejudice is told through an omnipresent narrator, aside from the witty remarks and insight into other characters it allows even though it's usually focused on Elizabeth, is how it plays on the audience's own prejudices and assumptions.

The narrator tells us very early on, chapter 4, that Darcy is "haughty, reserved, and fastidious, and his manners, though well-bred, were not inviting." We've already seen that when we meet him the previous chapter, and will see more of it in those following. But it's the readers, along with Elizabeth, who take that observation as not only a list of flaws (despite only the first actually being negative) but presumes even more damaging flaws must be attached to it. Darcy can be off-putting, especially so in the setting we meet him in: he dismissed Elizabeth within earshot of her, didn't engage with people attempting to converse with him, etc. It's easy to assume the worst of him in a world so driven by social niceties, and because we follow Elizabeth, who is so lively and playful amidst the rules which govern society. Elizabeth thinks he's bad tempered? It would make sense - he hasn't shown consideration for others much socially, why would he care when he's angry? He acted from resentment and jealousy and went against his father's will? That's not such a jump after the conclusion of a bad temper, his own acknowledgement of implacable resentment, and evidence of pride. The awareness of one offensive trait so naturally leads to prejudice against it, that we easily assume still worse qualities must exist. We are as mistaken as Elizabeth.

Even the idea that 'No, Darcy was never haughty or rude, he was just shy and misunderstood, the narrator is wrong' is just magnifying that prejudice. Yes, we do find out later that Darcy is not at ease among strangers, and was always intrinsically good; his morals and core values meant he was never as bad as Elizabeth believed. But that doesn't mean he was without flaws, and it's so fascinating that some analysis of his character seek to completely remove the negative traits which he eventually overcame after acknowledging them in himself. The logic seems to be that they feel if he had them in the start that he isn't actually such a good person. It's just another example of being so prejudiced against certain flaws that it's impossible for some people to reconcile that there doesn't have to be more serious failings attached, and someone can still be a good person despite being arrogant and not always nice. It's, ironically, being prejudiced in the exact same way that Elizabeth was at the start of the novel. It's amazing that Jane Austen was able to tap into that aspect of human nature so deftly, and invoke in both in her main character, and readers to this day.

Now, of course, the story is so well known it's rare for anyone to read it blind, so it's less likely anyone will be unaware of Darcy's good qualities despite first seeing his worst. Even if they do, Pride and Prejudice has become so genre defining that new readers who are the slightest bit genre savvy will be more aware than contemporary audiences were. But even if we know the story it's still so understandable why Elizabeth feels the way she does. We see what she sees and feel her conclusions make sense. Just as, even though the narrator tells us Darcy is starting to catch feelings for Elizabeth, we fully comprehend her not noticing and believing there's a mutual dislike. And though that is concrete evidence of Elizabeth not reading Darcy and his motives correctly, we are still so sympathetic of the basis of her prejudice that her continued belief in Darcy's lack of virtues makes sense from her point of view. We can see, as she later will, that she takes it too far, and should have noticed evidence to the contrary, but her prejudice against him based on his early behaviour and her pride at reading people correctly is so understandable.

Basically, in a story about the characters' pride and prejudices, I love, love, LOVE how the narrator's voice brings out those same traits in readers the exact same way we see it presenting in Elizabeth. We're all on that journey with her, and we can likewise learn the same lessons about ourselves as she does. Pride and Prejudice feels timeless, because even though society and thus the nuance changes, the book is about human nature, and that remains essentially the same.

[starduststudyblr]

just finished sex education s4 and the thing that stressed me out the most was why did the school let UNTRAINED TEENAGERS give therapy to their friends??? just bc they said they were “therapists”??? like did nobody at the school stop to think hmm maybe this isn’t the best idea

[knifekris]

every day i struggle to make choices

[considerad]

I'll be away from my studies, my applications, and my various little schemes for self-improvement for a whole month :)

[emgoesmed]

2/8/2023

Didactics on Zoom in the morning and then lunch with my M2 mentee :)

The abstract I submitted was not accepted which kinda sucks but that's how it goes sometimes... just gonna keep chugging along.

[mithliya]

btw there’s an anon who msged me to ask my thoughts on TRAs criticisms of the cass review. haven’t responded bc i’m very busy and such questions require more thoughtfulness on my part but hopefully i’ll have more of a chance to respond next week

[katierosefun]

second semester law school is really just. if “in the hall of the mountain king” was on loop for a whole semester.

[good--merits-accumulated]

[teabookgremlin]

somehow managed to both submit a job application without actually clicking submit or finishing the application and with my title set as dr. despite clicking on ms. as my title so needless to say i will not be getting that one

[shippingfangirl013]

How do people do it?

Our lives are just a string of beginnings and endings, thousands of changes every year, and yet, people are able to enjoy their lives? We’re able to laugh and cry and feel every emotion, and yet. . . Change still occurs.

After seeing the Barbie movie, it changed my perspective for the better.

But, at the same time, I started thinking about growing up and how, I’m an adult now, but I don’t want to be. I feel like it happened so fast that I’m stuck wishing I could go back to being a little girl without the worries that I have now. I don’t have as much time with my siblings now, and that scares me.

I don’t know how older people do it… how they continue on after the people they love have passed away? After their friends have passed away?

Friends moving hours away and you never see them again, when not even a year ago, you were roommates?

Pets that you love pass away, and you never know how much time you’ll have to spend with them?

Time just keeps passing and I don’t want to sit here, going to work 5 days a week, just to be excited to do what I want over a weekend…

[silver-sass]

Happy application submission day to all who are forced to celebrate.

[chemxpert]

Empowering Pharma Business Growth Worldwide | Chemxpert Database

Unlock new opportunities in business development pharma with Chemxpert Database. Connect with leading generic medicine manufacturers in India, renowned tablet manufacturing companies, and trusted API manufacturing companies in India. Explore collaborations with top pharma testing labs and innovative nutraceutical manufacturers to expand your portfolio. Chemxpert Database is your ultimate resource for navigating the pharmaceutical ecosystem, ensuring seamless partnerships and growth in the ever-evolving healthcare industry. Let’s innovate together!

[jcmarchi]

AI’s Life-Changing, Measurable Impact on Cancer

New Post has been published on https://thedigitalinsider.com/ais-life-changing-measurable-impact-on-cancer/

AI’s Life-Changing, Measurable Impact on Cancer

Leveraging Big Data to Enhance AI in Cancer Detection and Treatment

Integrating AI into the healthcare decision making process is helping to revolutionize the field and lead to more accurate and consistent treatment decisions due to its virtually limitless ability to identify patterns too complex for humans to see.

The field of oncology generates enormous data sets, from unstructured clinical histories to imaging and genomic sequencing data, at various stages of the patient journey. AI can “intelligently” analyze large-scale data batches at faster speeds than traditional methods, which is critical for training the machine learning algorithms that are foundational for advanced cancer testing and monitoring tools. AI also has tremendous inherent pattern recognition capabilities for efficiently modeling data set complexities. This is important because it enables deeper, multi-layered understandings of the impact of nuanced molecular signatures in cancer genomics and tumor microenvironments. Discovering a pattern between genes only found in a certain subset of cancer cases or cancer progression patterns can lead to a more tailored, patient-specific approach to treatment.

What is the ultimate goal?  AI-powered cancer tests that support clinical decision-making for doctors and their patients at every step of the cancer journey – from screening and detection, to identifying the right treatment, and for monitoring patients’ response to interventions and predicting recurrence.

Data Quality and Quantity: The Key to AI Success

Ultimately, an AI algorithm will only be as good as the quality of data that trains it. Poor, incomplete or improperly labeled data can hamstring AI’s ability to find the best patterns (garbage in, garbage out). This is especially true for cancer care, where predictive modeling relies on impeccable precision – one gene modification out of thousands, for example, could signal tumor development and inform early detection. Ensuring that high level of quality is time-consuming and costly but leads to better data, which results in optimal testing accuracy. However, developing a useful goldmine of data comes with significant challenges. For one, collecting large-scale genomic and molecular data, which can involve millions of data points, is a complex task. It begins with having the highest quality assays that measure these characteristics of cancer with impeccable precision and resolution.  The molecular data collected must also be as diverse in geography and patient representation as possible to expand the predictive capacity of the training models.  It also benefits from building long-term multi-disciplinary collaborations and partnerships that can help gather and process raw data for analysis. Finally, codifying strict ethics standards in data handling is of paramount importance when it comes to healthcare information and adhering to strict patient privacy regulations, which can sometimes present a challenge in data collection.

An abundance of accurate, detailed data will not only result in testing capabilities that can find patterns quickly and empower physicians with the best opportunity to address the unmet needs for their patients but will also improve and advance every aspect of clinical research, especially the urgent search for better medicines and biomarkers for cancer.

AI Is Already Showing Promise in Cancer Care and Treatment

More effective ways to train AI are already being implemented. My colleagues and I are training algorithms from a comprehensive array of data, including imaging results, biopsy tissue data, multiple forms of genomic sequencing, and protein biomarkers, among other analyses – all of which add up to massive quantities of training data. Our ability to generate data on the scale of quadrillions rather than billions has allowed us to build some of the first truly accurate predictive analytics in clinical use, such as tumor identification for advanced cancers of unknown primary origin or predictive chemotherapy treatment pathways involving subtle genetic variations.

At Caris Life Sciences, we’ve proven that extensive validation and testing of algorithms are necessary, with comparisons to real-world evidence playing a key role. For example, our algorithms trained to detect specific cancers benefit from validation against laboratory histology data, while AI predictions for treatment regimens can be cross compared with real-world clinical survival outcomes.

Given the rapid advancements in cancer research, experience suggests that continuous learning and algorithm refinement is an integral part of a successful AI strategy. As new treatments are developed and our understanding of the biological pathways driving cancer evolves, updating models with the most up-to-date information offers deeper insights and enhances detection sensitivity.

This ongoing learning process highlights the importance of broad collaboration between AI developers and the clinical and research communities. We’ve found that developing new tools to analyze data more rapidly and with greater sensitivity, coupled with feedback from oncologists, is essential. Bottom-line: the true measure of an AI algorithm’s success is how accurately it equips oncologists with reliable, predictive insights they need and how adaptable the AI strategy is to ever-changing treatment paradigms.

Real-World Applications of AI Are Already Increasing Survival Rates and Improving Cancer Management

Advances in data scale and quality have already had measurable impacts by expanding the physician decision-making toolkit, which has had real-world positive results on patient care and survival outcomes. The first clinically validated AI tool for navigating chemotherapy treatment choices for a difficult-to-treat metastatic cancer can potentially  extend patient survival by 17.5 months, compared to standard treatment decisions made without predictive algorithms1. A different AI tool can predict with over 94% accuracy the tumor of origin for dozens of metastatic cancers2 – which is critical to creating an effective treatment plan.  AI algorithms are also predicting how well a tumor will respond to immunotherapy based on each person’s unique tumor genetics. In each of these cases, AI toolkits empower clinical decision-making that improves patient outcomes compared with current standards of care.

Expect An AI Revolution in Cancer

AI is already changing how early we can detect cancer and how we treat it along the way. Cancer management will soon have physicians working side-by-side with integrated AI in real time to treat and monitor patients and stay one step ahead of cancer’s attempts to outwit medicines with mutations. In addition to ever-improving predictive models for detecting cancer earlier and providing more effective personalized treatment paradigms, physicians, researchers, and biotech companies are hard at work today to leverage data and AI analyses to drive new therapeutic discoveries and molecular biomarkers for tomorrow.

In the not-too-distant future, these once-impossible advances in AI will reach far beyond cancer care to all disease states, ending an era of uncertainty and making medicine more accurate, more personalized, and more effective.