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D R
M A N I S H
RAJPUT
ht tps://drmanishrajput.com
Book an appointme
nt!
IN T R O D U C T IO
N
Dr
. Manish Rajput is an
Interventional Radiologist & Team
Lead, Team IR Jaipur
. They are the
biggest team of Interventional
Radiologists. They are trained from
Tata Memorial Center, Mumbai,
India. They have worked in so
many government and corporate
hospitals across the country.
Medical school (MBBS): 2005-2011: -
People’s Medical College, Bhopal(MP)
DNB (Radio diagnosis):- Apollo
hospital, Hyderabad(Telangana)
FVIR (PDCC): - Tata Memorial
Centre, Mumbai(Maharashtra)
Senior Resident: Hinduja Hospital Mumbai,
SMS Hospital Jaipur
Past Visiting Doctor: Leelavati Hospital
Mumbai, Breach Candy Hospital Mumbai,
Wockhardt Hospital Mumbai, Hinduja
Hospital Mumbai
Ex Assitant Professor: JNU Medical College,
Jaipur Currently Working as Senior Consultant
Interventional Radiologist in various
corporate hospitals of Rajasthan based in
Jaipur
HIS
EDUCATION
S T R E N G T H S
I lead the biggest IR team in the
state. Vast portfolio for IR
services.
All the team members are from
Tata Memorial Hospital, Mumbai.
Extensive experience in performing
and interpreting basic Radio-
Diagnosis.
Gained experience in performing
Interventional Radiologic
procedures. I possess oratory
skill by speaking at numerous
industry events.
Ability to teach complex concepts in a
basic manner
.
Varicose Vein
s
Prostate Artery
Embolization
PRG
Biopsy an
d fNAC
Angioplasty & Venoplast
y
PCN & DJ Stentin
g
O
U
R
S
E
R
V
+91 7729021111
dr.manish@infinityintervention.com
O-5-A, Adinath Marg, Near Surya
Hospital, C Scheme, Ashok
Nagar, Jaipur, Rajasthan 302001
C ON TA C
T US!

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Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, B... by Oleg Kshivets, has 29 slides with 265 views. METHODS: We analyzed data of 786 consecutive LCP (age=57.7±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2025 (m=674, f=112; upper lobectomies=284, lower lobectomies=180, middle lobectomies=18, bilobectomies=46, pneumonectomies=258, mediastinal lymph node dissection=786; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=199; only surgery-S=629, adjuvant chemoimmunoradiotherapy-AT=157: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=328, T2=260, T3=137, T4=61; N0=528, N1=133, N2=125, M0=786; G1=199, G2=248, G3=339; squamous=423, adenocarcinoma=313, large cell=50; early LC=221, invasive LC=565; right LC=422, left LC=364; central=298; peripheral=488. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence. RESULTS: Overall life span (LS) was 2245.9±1741.5 days and cumulative 5-year survival (5YS) reached 73.4%, 10 years – 65.2%, 20 years – 42.5%. 516 LCP lived more than 5 years (LS=3118.2±1527.7 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.2% vs.63.5%, P=0.00001 by log-rank test). AT significantly improved 5YS (65.6% vs. 34.8%) (P=0.00001 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, AT, blood cell circuit, prothrombin index, age, bilirubin, procedure type (P=0.000-0.044). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), healthy cells/CC (4), eosinophils/CC (5), erythrocytes/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); stick neutrophils (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) p
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Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analy... by Oleg Kshivets, has 25 slides with 298 views.We analyzed data of 568 consecutive ECP (age=56.7±9 years; tumor size=5.9±3.5 cm) radically operated (R0) and monitored in 1975-2025 (m=424, f=144; esophagogastrectomies (EG) Garlock=290, EG Lewis=278, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=174; adenocarcinoma=326, squamous=232, mix=10; T1=133, T2=121, T3=186, T4=128; N0=288, N1=71, N2=209; G1=161, G2=143, G3=264; early EC=114, invasive=454; only surgery=431, adjuvant chemoimmunoradiotherapy-AT=137: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. RESULTS: Overall life span (LS) was 1906.3±2278.4 days and cumulative 5-year survival (5YS) reached 53%, 10 years – 46.4%, 20 years – 33.4%, 30 years – 27.5%. 194 ECP lived more than 5 years (LS=4300.8±2503.5 days), 105 ECP – more than 10 years (LS=5860.8±2469.2 days). 232 ECP died because of EC (LS=628.8±321.8 days). AT significantly improved 5YS (60.3% vs. 43.1%) (P=0.007 by log-rank test). 5YS of ECP of upper/3 was significantly better than others (65.3% vs.50.3%) (P=0.003). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, blood cell subpopulation, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), EC cell dynamics, T, G, histology, age, localization, prothrombin index, coagulation time, residual nitrogen, chlorides (P=0.000-0.047). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and healthy cells/CC (rank=1), erythrocytes/CC (2), PT N0—N12 (3), PT early-invasive EC (4), thrombocytes/CC (5); segmented neutrophils/CC (6), lymphocytes/CC (7), eosinophils/CC (8), stick neutrophils/CC (9), leucocytes/CC (10), monocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC cell dynamics; 9) EC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of sufficient quantity of very experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
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25 slides298 views
Artificial Intelligence in Oncology: Transforming Cancer Carepptx by NEIGRIHMS, SHILLONG, has 60 slides with 314 views.Artificial Intelligence (AI) is transforming oncology by enabling faster, more accurate, and personalized cancer care. AI uses technologies like machine learning (ML), deep learning (DL), and natural language processing (NLP) to analyze complex medical data, helping doctors make better decisions at every stage of cancer care. Key Applications of AI in Oncology: Cancer Detection & Diagnosis: AI analyzes radiology (CT, MRI, mammography) and pathology images to detect tumors early and accurately. Tools like PathAI, Aidoc, and DeepMind are used in clinical imaging. Precision Medicine & Genomics: AI interprets genetic mutations to match patients with targeted therapies. Platforms like Tempus and OncoKB support personalized cancer treatment. Radiation Oncology: AI automates contouring, treatment planning, and dose optimization. Reduces planning time and improves consistency in radiation delivery. Drug Discovery & Clinical Trials: AI helps discover new cancer drugs and match patients to trials. Companies like BenevolentAI and Insilico Medicine lead this space. Prognostics & Monitoring: AI predicts survival, recurrence, and side effects using patient data. Wearables and mobile apps track symptoms and alert doctors in real time. Benefits of AI in Oncology: Early and accurate diagnosis Faster workflows and reduced workload Personalized treatments Improved patient outcomes Challenges: Data privacy and bias Lack of clinical validation Interpretability of AI decisions Integration into hospital systems Conclusion: AI is not replacing oncologists but empowering them with better tools to diagnose, plan, and treat cancer more effectively. With ongoing research and responsible use, AI will play a crucial role in the future of oncology.
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LDMMIA Reiki Yoga S4 Bonus S2 Clearing Chi by LDM Mia eStudios, has 12 slides with 362 views.Happy May and Happy Weekend, My Guest Students. Weekends seem more popular for Workshop Class Days lol. These Presentations are timeless. Tune in anytime, any weekend. A 4TH FREE WORKSHOP/ BONUS SESSION 2 Reiki Yoga “Clearing” Our Sessions 1-3 are available for download notes. Thx for Reading. https://ko-fi.com/ldmmia Celebrating my 49th Bday. A Taurus Sun, Born early May 3rd, “76”. Also A Gemini Moon/Rising. I follow Both signs. Welcome to the 2nd Bonus Session. Beyond Basics - Good Vibes Only: —Review - Good Vibes Only: — For me, within both Reiki and Yoga sessions the essentials boost the energy. Energy can also be called Vibrations and Frequency. So many coaches are specializing within Frequency topics. They can coach entire themes using Frequency success stories. This shows how little we think of energy? We need our coaches to boost our wisdom? To boost the vibes? For Reiki & Yoga Therapy, using ‘Props’ can assist, protect, and heal energies - faster/better. Let’s Explore more. (See Presentation for all sections, THX) Clear Your Energy Pt 1…(See Presentation) Clear Your Energy - Pt 2 I know we operate busy schedules. Sometimes I will yoga stretch, do warm ups, Fuse Qigong, and clear my chakras. It can be therapy or for energy boosts. So many things within our activities will leave behind energy. This can be positive or negative. We assume these energies naturally drop off. But, not always the case. Some energies latch on longterm. This all depends on your moods, emotions, and lifestyle. Hope it makes sense. We have to monitor our energy intake/out-take. Repost: Taking breaks, pausing, relaxing, are common things ppl struggle with. Including at times, myself. Reiki requires chill hours or meditations. We often believe our schedules are badges to display for social/approval? This is a generational society belief. It takes courage to bold/quietly declare - the opposite. (Old Matrix Systems) Energy Monitoring-The Media/News A Perm bonus section I wanted to keep. This is about The media and news. Now, I understand it’s hard to avoid all news. Especially when we need our global, local, weather, and economic updates. Some news are important while others are extremely negative. Anything hosting bad vibes can be draining. I have seen this occur within distant/visual updates like news or gossip. We have to keep what we need. Then leave behind what we don’t. The intuitive coaching/Tarot rules. There’s a lot going on for every country. So now is the time to practice calming methods for daily life or emergencies. (See Presentation for all, new topics, THX) To Donate/Tip/Love Offerings: ♥¸.•♥ ♥¸.•♥ - https://ko-fi.com/ldmmia - CashApp: $ldmmia2 or https://ldmchapels.weebly.com Public Social: https://www.instagram.com/chelleofsl/ https://x.com/OnlineDrLeZ
LDMMIA Reiki Yoga S4 Bonus S2 Clearing ChiLDMMIA Reiki Yoga S4 Bonus S2 Clearing Chi
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Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, B... by Oleg Kshivets, has 29 slides with 265 views. METHODS: We analyzed data of 786 consecutive LCP (age=57.7±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2025 (m=674, f=112; upper lobectomies=284, lower lobectomies=180, middle lobectomies=18, bilobectomies=46, pneumonectomies=258, mediastinal lymph node dissection=786; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=199; only surgery-S=629, adjuvant chemoimmunoradiotherapy-AT=157: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=328, T2=260, T3=137, T4=61; N0=528, N1=133, N2=125, M0=786; G1=199, G2=248, G3=339; squamous=423, adenocarcinoma=313, large cell=50; early LC=221, invasive LC=565; right LC=422, left LC=364; central=298; peripheral=488. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence. RESULTS: Overall life span (LS) was 2245.9±1741.5 days and cumulative 5-year survival (5YS) reached 73.4%, 10 years – 65.2%, 20 years – 42.5%. 516 LCP lived more than 5 years (LS=3118.2±1527.7 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.2% vs.63.5%, P=0.00001 by log-rank test). AT significantly improved 5YS (65.6% vs. 34.8%) (P=0.00001 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, AT, blood cell circuit, prothrombin index, age, bilirubin, procedure type (P=0.000-0.044). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), healthy cells/CC (4), eosinophils/CC (5), erythrocytes/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); stick neutrophils (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) p
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DR MANISH- ppt Laser Proctology piles & Fistula

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  • 2. IN T R O D U C T IO N Dr . Manish Rajput is an Interventional Radiologist & Team Lead, Team IR Jaipur . They are the biggest team of Interventional Radiologists. They are trained from Tata Memorial Center, Mumbai, India. They have worked in so many government and corporate hospitals across the country.
  • 3. Medical school (MBBS): 2005-2011: - People’s Medical College, Bhopal(MP) DNB (Radio diagnosis):- Apollo hospital, Hyderabad(Telangana) FVIR (PDCC): - Tata Memorial Centre, Mumbai(Maharashtra) Senior Resident: Hinduja Hospital Mumbai, SMS Hospital Jaipur Past Visiting Doctor: Leelavati Hospital Mumbai, Breach Candy Hospital Mumbai, Wockhardt Hospital Mumbai, Hinduja Hospital Mumbai Ex Assitant Professor: JNU Medical College, Jaipur Currently Working as Senior Consultant Interventional Radiologist in various corporate hospitals of Rajasthan based in Jaipur HIS EDUCATION
  • 4. S T R E N G T H S I lead the biggest IR team in the state. Vast portfolio for IR services. All the team members are from Tata Memorial Hospital, Mumbai. Extensive experience in performing and interpreting basic Radio- Diagnosis. Gained experience in performing Interventional Radiologic procedures. I possess oratory skill by speaking at numerous industry events. Ability to teach complex concepts in a basic manner .
  • 5. Varicose Vein s Prostate Artery Embolization PRG Biopsy an d fNAC Angioplasty & Venoplast y PCN & DJ Stentin g O U R S E R V
  • 6. +91 7729021111 dr.manish@infinityintervention.com O-5-A, Adinath Marg, Near Surya Hospital, C Scheme, Ashok Nagar, Jaipur, Rajasthan 302001 C ON TA C T US!